Assessment of cloud hosting suitability for multiple applications

ABSTRACT

In accordance with the teachings of the present disclosure, a method of assessment of cloud hosting suitability for multiple applications is disclosed. The method may include creating a second synthetic application definition based on a first synthetic application definition, wherein creating the second application definition comprises defining, in the second synthetic application definition, a second plurality of resource consumptions, wherein the second plurality of resource consumptions are equivalent to consumptions by the candidate application at a second level of user demand. The method may also include consuming, based on the second synthetic application definition, a plurality of quantities of resources of the computing system and evaluating the computing system. The present disclosure additionally includes associated systems and apparatuses.

CROSS-REFERENCE TO RELATED APPLICATION

The present application is a continuation application of copending U.S.patent application Ser. No. 14/245,711 filed Apr. 4, 2014, which ishereby incorporated by reference in its entirety for all purposes.

BACKGROUND

The present disclosure relates generally to information servicesinfrastructure and network management, and more specifically, toapplication-specific assessment of cloud hosting suitability of nodes ofa computer system. Computer systems may include many nodescommunicatively coupled to one another via a network. Application coderuns on computer systems. One application may have code running onvarious nodes of a computer system. Such a group of nodes may bereferred to as a cloud.

Computing capacity of clouds may be used to run a variety ofapplications. However, computing capacity may be constrained byavailability of one or more resources of nodes of the cloud, and infact, may be insufficient to provide quality performance of a particularapplication. The present disclosure relates generally to systems andmethods for application-specific assessment of cloud hostingsuitability.

BRIEF SUMMARY

A method is disclosed, including defining a first plurality of resourceconsumptions in a first synthetic application definition, wherein thefirst plurality of resource consumptions are equivalent to consumptionsby a candidate application at a first level of user demand. The methodmay also include distributing the first synthetic application definitionto a synthetic application. Additionally, the method may includeconsuming, with the synthetic application and based on the firstsynthetic application definition, a first plurality of quantities ofresources of a plurality of nodes of a computing system. Further, themethod may include recording a first performance of the syntheticapplication. The method may additionally include creating a secondsynthetic application definition based on the first syntheticapplication definition, wherein creating the second applicationdefinition comprises defining, in the second synthetic applicationdefinition, a second plurality of resource consumptions, wherein thesecond plurality of resource consumptions are equivalent to consumptionsby the candidate application at a second level of user demand. Themethod may also include distributing the second synthetic applicationdefinition to the synthetic application. Further, the method may includeconsuming, with the synthetic application and based on the secondsynthetic application definition, a second plurality of quantities ofresources of the plurality of nodes of the computing system. The methodmay include recording a second performance of the synthetic applicationand evaluating the computing system based upon the first performance andthe second performance.

A computer-readable storage medium, including computer-executableinstructions carried on the computer readable medium is disclosed. Theinstructions readable by a processor and, when read and executed,configured to cause the processor to define a first plurality ofresource consumptions in a first synthetic application definition,wherein the first plurality of resource consumptions are equivalent toconsumptions by a candidate application at a first level of user demandand to distribute the first synthetic application definition to asynthetic application.

The instructions may be further configured to cause the processor toconsume, with the synthetic application and based on the first syntheticapplication definition, a first plurality of quantities of resources ofa plurality of nodes of a computing system and to record a firstperformance of the synthetic application. Additionally, the instructionsmay be further configured to cause the processor to create a secondsynthetic application definition based on the first syntheticapplication definition, wherein creating the second applicationdefinition comprises defining, in the second synthetic applicationdefinition, a second plurality of resource consumptions, wherein thesecond plurality of resource consumptions are equivalent to consumptionsby the candidate application at a second level of user demand. Theinstructions may be further configured to cause the processor todistribute the second synthetic application definition to the syntheticapplication, to consume, with the synthetic application and based on thesecond synthetic application definition, a second plurality ofquantities of resources of the plurality of nodes of the computingsystem, and to record a second performance of the synthetic application.The instructions may also be configured to cause the processor toevaluate the computing system based upon the first performance and thesecond performance.

An apparatus for assessing cloud hosting suitability of a plurality ofnodes of a computer system is disclosed. The apparatus including aprocessor, a memory communicatively coupled to the processor. The memoryincludes instructions that are operable, when executed for causing theprocessor to define a first plurality of resource consumptions in afirst synthetic application definition, wherein the first plurality ofresource consumptions are equivalent to consumptions by a candidateapplication at a first level of user demand. The instructions may befurther configured to cause the processor to distribute the firstsynthetic application definition to a synthetic application. Theprocessor may additionally consume, with the synthetic application andbased on the first synthetic application definition, a first pluralityof quantities of resources of a plurality of nodes of a computing systemand record a first performance of the synthetic application. Theprocessor may be further configured to create a second syntheticapplication definition based on the first synthetic applicationdefinition, wherein creating the second application definition comprisesdefining, in the second synthetic application definition, a secondplurality of resource consumptions, wherein the second plurality ofresource consumptions are equivalent to consumptions by the candidateapplication at a second level of user demand. Additionally, theprocessor may be configured to distribute the second syntheticapplication definition to the synthetic application, to consume, withthe synthetic application and based on the second synthetic applicationdefinition, a second plurality of quantities of resources of theplurality of nodes of the computing system and to record a secondperformance of the synthetic application. The processor may beconfigured to evaluate the computing system based upon the firstperformance and the second performance.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the configurations of the presentdisclosure, needs satisfied thereby, and the objects, features, andadvantages thereof, reference now is made to the following descriptiontaken in connection with the accompanying drawings.

FIG. 1 is a block diagram depicting an exemplary system forapplication-specific assessment of cloud hosting suitability, inaccordance with the teachings of the present disclosure.

FIG. 2 is an illustration of a synthetic application, in accordance withthe teachings of the present disclosure.

FIG. 3 is an illustration of a synthetic application definition, inaccordance with the teachings of the present disclosure.

FIG. 4 is an illustration of node properties, in accordance with theteachings of the present disclosure.

FIG. 5 is an illustration of the operation of a system for performingapplication-specific assessment of cloud hosting suitability, inaccordance with the teachings of the present disclosure.

FIG. 6 is a flowchart of an exemplary method for performingapplication-specific assessment of cloud hosting suitability, inaccordance with the teachings of the present disclosure.

FIGS. 7A and 7B are illustrations of an exemplary system for performingapplication-specific assessment of cloud hosting suitability formultiple applications, in accordance with teachings of the presentdisclosure.

FIG. 8 is a flowchart of an exemplary method for performingapplication-specific assessment of cloud hosting suitability formultiple applications, in accordance with teachings of the presentdisclosure.

FIG. 9 is an illustration of an exemplary system for performingapplication-specific assessment of cloud hosting suitability of multipleclouds, in accordance with teachings of the present disclosure.

FIG. 10 is a flowchart of an exemplary method for performingapplication-specific assessment of cloud hosting suitability of multipleclouds, in accordance with teachings of the present disclosure.

FIG. 11 is an illustration of an exemplary system for performingapplication-specific assessment of cloud hosting suitability formultiple applications in a node of a cloud, in accordance with teachingsof the present disclosure.

FIG. 12 is a flowchart of an exemplary method for performingapplication-specific assessment of cloud hosting suitability of multipleapplications in a node of a cloud, in accordance with teachings of thepresent disclosure.

FIG. 13 is an illustration of an exemplary system for performingservice-level agreement assessment of a cloud, in accordance withteachings of the present disclosure.

FIG. 14 is a flowchart of an exemplary method for performingservice-level agreement assessment of a cloud, in accordance withteachings of the present disclosure.

DETAILED DESCRIPTION

As will be appreciated by one skilled in the art, aspects of the presentdisclosure may be illustrated and described herein in any of a number ofpatentable classes or context including any new and useful process,machine, manufacture, or composition of matter, or any new and usefulimprovement thereof. Accordingly, aspects of the present disclosure maybe implemented entirely hardware, entirely software (including firmware,resident software, micro-code, etc.) or combining software and hardwareimplementation that may all generally be referred to herein as a“circuit,” “node,” “element,” “module,” “component,” or “system.”Furthermore, aspects of the present disclosure may take the form of acomputer program product embodied in one or more computer readable mediahaving computer readable program code embodied thereon.

Any combination of one or more computer readable media may be utilized.The computer readable media may be a computer readable signal medium ora computer readable storage medium. A computer readable storage mediummay be, for example, but not limited to, an electronic, magnetic,optical, electromagnetic, or semiconductor system, apparatus, or device,or any suitable combination of the foregoing. More specific examples (anon-exhaustive list) of the computer readable storage medium wouldinclude the following: a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an appropriateoptical fiber with a repeater, a portable compact disc read-only memory(CD-ROM), a digital versatile disk (DVD), an optical storage device, amagnetic storage device, or any suitable combination of the foregoing.In the context of this document, a computer readable storage medium maybe any tangible medium that can contain, or store a program for use byor in connection with an instruction execution system, apparatus, ordevice.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device. Program codeembodied on a computer readable signal medium may be transmitted usingany appropriate medium, including but not limited to wireless, wireline,optical fiber cable, RF, etc., or any suitable combination of theforegoing.

Computer program code for carrying out operations for aspects of thepresent disclosure may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB.NET,Python or the like, conventional procedural programming languages, suchas the “C” programming language, Visual Basic, Fortran 2003, Perl, COBOL2002, PHP, ABAP, dynamic programming languages such as Python, Ruby andGroovy, or other programming languages. The program code may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider) or in a cloud computing environment or offered as aservice such as a Software as a Service (SaaS).

Aspects of the present disclosure are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatuses(systems) and computer program products according to embodiments of thedisclosure. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable instruction executionapparatus, create a mechanism for implementing the functions/actsspecified in the flowchart and/or block diagram block or blocks.

The computer program instructions may also be stored in a computerreadable medium that when executed can direct a computer, otherprogrammable data processing apparatus, or other devices to function ina particular manner, such that the instructions when stored in thecomputer readable medium produce an article of manufacture includinginstructions which when executed, cause a computer to implement thefunction/act specified in the flowchart and/or block diagram block orblocks. The computer program instructions may also be loaded onto acomputer, other programmable instruction execution apparatus, or otherdevices to cause a series of operational steps to be performed on thecomputer, other programmable apparatuses or other devices to produce acomputer implemented process such that the instructions which execute onthe computer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

In accordance with the teachings of the present disclosure, a system maybe provided that is configured to provide application-specificassessment of cloud hosting suitability. Particular embodiments andtheir advantages are best understood by reference to FIGS. 1 through 14,wherein like numbers are used to indicate like and corresponding parts.

FIG. 1 is a block diagram depicting an exemplary system 100 forapplication-specific assessment of cloud hosting suitability, inaccordance with the teachings of the present disclosure. System 100 mayinclude, for example, a plurality of nodes 115, network 120, and localnetworks 121. For example, each node 115 may include a server (e.g.,blade server or rack server), personal computer (e.g., desktop orlaptop), tablet computer, mobile device (e.g., personal digitalassistant (PDA) or smart phone), network storage device, printer,switch, router, data collection device, virtual machine, script,executable, firmware, library, shared library, function, module,software application, or any other suitable device or application. Thecomponents or whole of node 115 may make up a resource. Furthermore,node 115 may include one or more resources, such as a processor, memory,peripheral, application, datastore, storage, function, card, board, orother physical or virtual device. Resources of nodes 115 may furtherinclude resources of network 120 connected to nodes 115, for exampledata transmission bandwidth, network connectivity, or any othercomponents or functionality of network 120 or local networks 121.Although exemplary system 100 is shown in FIG. 1 as including aparticular number of nodes 115, a system may include more than or fewerthan the number of nodes 115 illustrated. Similarly, although exemplarysystem 100 is shown in FIG. 1 as including nodes 115 of particulartypes, a system may include nodes 115 of types other than those shown inFIG. 1.

Network 120 may include a network and/or fabric configured tocommunicatively couple nodes 115, synthetic applications 130, and/or anynode associated with system 100. Network 120 may be implemented as, ormay be a part of, a storage area network (SAN), personal area network(PAN), local area network (LAN), a metropolitan area network (MAN), awide area network (WAN), a wireless local area network (WLAN), a virtualprivate network (VPN), an intranet, the Internet or any otherappropriate architecture or system configured to facilitate thecommunication of signals, data and/or messages (generally referred to asdata). Network 120 may transmit data using any storage and/orcommunication protocol, including without limitation, Fibre Channel,Frame Relay, Asynchronous Transfer Mode (ATM), Internet protocol (IP),other packet-based protocol, small computer system interface (SCSI),Internet SCSI (iSCSI), advanced technology attachment (ATA), serial ATA(SATA), advanced technology attachment packet interface (ATAPI), serialstorage architecture (SSA), integrated drive electronics (IDE), and/orany combination thereof. Network 120 and its various components may beimplemented using hardware, software, or any combination thereof. Localnetworks 121 are typically implemented as local area networks, but maybe implement as or part of any type of network, such as network 120. Insome embodiments, local networks 120 may be implemented as components ofnetwork 120.

One or more nodes 115 may be disposed to host computer applications. Forexample, one or more nodes 115 may be disposed to host enterpriseapplications, including, but not limited to, internet web page hosting,internet based applications, database applications, e-commerceapplications, or any other suitable application or combination ofapplications. Users of such applications may access nodes 115 disposedfor hosting the application by using, for example, network 120 or localnetworks 121. A group of nodes 115 accessible via network 120 or localnetworks 121 may be referred to as cloud 125. For example, nodes 115A,115B, 115C, and 115D may be jointly disposed to host applications. Nodes115A, 115B, 115C, and 115D may be referred to collectively as cloud125A. In some embodiments, nodes 115A, 115B, 115C, and 115D in cloud125A may be interconnected by local network 121A. In other embodiments,nodes 115 in a cloud 125 may be interconnected by any other suitableconnection, such as network 120 or local networks 121. Likewise, nodes115E, 115F, 115G, and 115H may make up some or all of a different cloud125B. In some embodiments, nodes 115E, 115F, 115G, and 115H in cloud125B may be interconnected by local network 121B. In other embodiments,nodes 115 in a cloud 125 may be interconnected by any other suitableconnection, such as network 120. Clouds 125 may include any number ofnodes 115, and a single instance of node 115 may be included in one ormore clouds. Nodes 115 in clouds 125 may be physically and/or logicallydistinct from other nodes 115 in clouds 125.

Cloud-based applications may include applications or groups ofapplications hosted on one or more clouds 125. Operators of clouds 125may select particular cloud-based applications to be hosted by clouds125, or may sell or give access to resources of clouds 125 tothird-party customers. Clouds 125 may host any suitable number ofapplications at a particular time, including applications hosted for thebenefit of one or more third-party customers.

Operators of clouds 125 may, for example, offer to sell Infrastructureas a Service (IaaS). Frequently, clouds 125 include one or more nodes115 capable of hosting computer program code representing a virtualmachine. Third-party customers may provide computer program coderepresenting a virtual machine including one or more applications orportions of applications. Operators of clouds 125 may implement suchcomputer program code on a particular physical machine. Implementingcomputer program code representing a virtual machine may be referred as“standing up” a virtual machine in a host. Clouds 125 may includephysical machines configured to host virtual machines provided bydifferent third-party customers.

Different nodes 115 in clouds 125 may include different resources. Somenodes 115 may include resources optimized for particular functions. Forexample, a particular node 115 intended for implementing a database mayinclude above average storage resources and/or network resources. Aparticular node 115 intended for implementing graphics processing mayinclude above average computer processing resources. Nodes 115 may, forexample, be provisioned with resources optimized for particular tasks,or may be provisioned with any suitable group of resources.

Different cloud-based applications may consume different resources ofnodes 115 and/or of clouds 125. Consuming or utilizing resources mayinclude, for example, performing operations with, or otherwiseexercising the functionality of a node or of a component of a node. Forexample, websites hosted in a computing system might require substantialnetwork bandwidth to enable large numbers of users to simultaneouslyaccess the website. A computing system hosting a database applicationmay require substantial throughput in read and write operations to astorage system. Likewise, a computing system hosting a graphicsprocessing system may require substantial computer processing and/ormemory resources to complete processing requests. If nodes 115 of clouds125 have different amounts and/or types of available resources, oneinstance of cloud 125 may be more suitable for hosting a specificapplication than another instance of cloud 125. In some embodiments,availability of resources may depend on hardware configuration of anode. In other embodiments, availability of resources may depend oninteractions with other applications running on a node. Syntheticapplications 130 may be used to determine whether nodes 115 of clouds125 are suitable for hosting a particular application or portion ofapplication.

In some embodiments, synthetic applications 130 may be used to evaluateexpected performance of one or more real-world cloud-based applicationshosted on clouds 125. Typically, resources consumed by cloud-basedapplications may be described in terms of functionality or flow.Functionality or flow of a real-world application may, for example,include sequences of resource consumptions within particular nodes 115and/or between one or more nodes 115. For example, one component of thefunctionality or flow of an exemplary cloud-based real-world applicationmay include a user logging into a bank account on a website andretrieving account details. Such functionality or flow may include anode hosting a webpage which, upon receipt of a login request, queries adatabase of account details in another node. Real-world applications maybe characterized by creating synthetic application definitions includingbusiness functions resembling the functionality or flow of thesereal-world applications. Business functions may specify sequences ofresource consumptions. The functionality or flow of real-worldapplications may be emulated by configuring synthetic applications 130to perform sequences of resource consumptions, as specified in businessfunctions, based upon synthetic application definitions.

Synthetic applications may be configured to effectuate various types ofresource consumptions. In some embodiments, synthetic applications maybe configured to consume resources of a cloud responsive to a syntheticapplication definition based upon a real-world application. In otherembodiments, synthetic applications may be configured to consumeresources of a cloud responsive to multiple synthetic applicationdefinitions based upon behavior of real-world application at differentlevels of user demand. In further embodiments, synthetic applicationsmay be configured to consume resources of multiple clouds responsive toa synthetic application definition based upon behavior of real-worldapplication. In other embodiments, multiple synthetic applications maybe configured to consume resources of a node of a cloud responsive tosynthetic application definitions based upon behavior of multiplereal-world applications. Although particular uses of syntheticapplications are described, it will be understood that syntheticapplication may be used in any suitable configuration, includingcombinations of configurations described herein.

In one embodiment, synthetic applications 130 may be used to performapplication-specific assessments of cloud hosting suitability. Each node115 may include one or more instances of synthetic application 130. Eachsynthetic application 130 within a node 115 may include a physical orlogical node communicatively coupled to other synthetic applications 130within other nodes 115 via network 120. Synthetic applications 130 maybe configured to consume resources of nodes 115 as they are configuredwithin system 100.

FIG. 2 is an illustration of a synthetic application 130, in accordancewith the teachings of the present disclosure. FIG. 2 illustrates anexemplary node 115 containing a synthetic application 130. In someembodiments of the invention, nodes 115 may include processor 205,memory 210, storage device 220, and/or network interface 230. Instancesof synthetic application 130 may include synthetic application module215. Instances of synthetic application 130 may further includesynthetic application definition 225, and/or node properties 360.Although node 115 is illustrated as including processor 205, memory 210,and storage device 220, node 115 may include any suitable number or kindof resources that may be used by synthetic application 130.

Processor 205 may be communicatively coupled to memory 210 and syntheticapplication module 215. Processor 205 may include any system, device, orapparatus operable to interpret and/or execute program instructionsand/or process data, and may include, without limitation, amicroprocessor, a microcontroller, a digital signal processor (DSP), anapplication specific integrated circuit (ASIC), or any other digital oranalog circuitry configured to interpret and/or execute programinstructions and/or process data.

Synthetic application module 215 may include computer-programinstructions resident in memory 210 (or another computer-readable mediumcommunicatively coupled to synthetic application 130) and capable ofbeing executed by processor 205. Memory 210 may be configured in part orwhole as application memory, system memory, or both. Memory 210 mayinclude any system, device, or apparatus configured to hold and/or houseone or more memory modules. Each memory module may include any system,device or apparatus configured to retain program instructions and/ordata for a period of time (e.g., computer-readable storage media). Thecomputer-program instructions resident in memory 210, when executed byprocessor 205 may perform the functionality of synthetic application 130or synthetic application module 225, as described herein.

Synthetic application module 215 may further include computer-programinstructions configured to characterize total processing power capacityof nodes 115. Total processing power capacity may describe a platformindependent amount of processing resource consumptions that a particularnode 115 is capable of performing in a period of time. Typically, aparticular real-world application may take different amounts of time toexecute operations or portions of computer program code on differentnodes 115. For example, if a first node 115 has a particular totalprocessing power capacity, and a second node 115 has a particular totalprocessing power capacity twice that of the first node 115, a particularset of computer-program instructions may, in the absence of interferencefrom other sets of computer-program instructions, execute approximatelytwice as fast on the second node 115 as the first node 115. In part,this difference may arise because different nodes 115 may have differentresource provisions. For example, nodes 115 may have different amountsof processing resources, memory resources, storage resources, networkresources, and/or other resources related to infrastructure assets thatcan be described in terms of quantity and/or rate and/or usage ofcomponents nodes 115.

In some embodiments, synthetic applications modules 215 may beconfigured to determine total processing power capacity of a node 115.Typically, processing speed of processors, such as processor 205, may belimited by one or more different types of processing resourceconsumptions. For example, processing speed may be limited by capacitiesof floating point units, sizes of various caches, sets of registers,various busses, or any other component, element, module or functionalityof any component of node 115. In some embodiments, to determine totalprocessing power capacity, synthetic application module 215 may executemultiple loops of a set of computer-program instructions. Each loop mayperform one or more instances of a variety of typical processingresource consumptions, such as floating point calculations, Fibonaccicalculations, sorting tasks, “card shuffling” tasks, data compressionand decompression tasks, prime number calculations, sequence searching,or any other suitable type of processing resource consumption. Each typeof processing resource consumption may have an associated weighting sothat more, fewer, or equal processing resources are consumed for thattype of processing resource consumption per loop as compared to othertypes. In some embodiments, the weightings may be adjusted and theimplementation may be run on various architectures until the resourcesconsumed by executing computer-program instructions based on theresulting set of weightings are proportional to total processing powercapacity.

Synthetic application modules 215 may be configured to consume resourcesof nodes 115 in any suitable manner or degree, such as a similar manneror degree as a real-world application or group of applications wouldconsume resources of nodes 115. Such resources may include, but are notlimited to, processing resources, memory resources, storage resources,network resources, and/or other resources related to infrastructureassets that can be described in terms of quantity and/or rate and/orusage of components nodes 115. Synthetic applications modules 215 may befurther configured to issue requests via network 120 for other instancesof synthetic application 130 to consume resources of nodes 115.Synthetic applications modules 215 may be configured to issue repliesvia network 120, after consuming resources in response to a request.Where a single resource is referenced, it may be understood thatmultiple resources may be consumed.

Synthetic application modules 215 may be configured to collect datacorresponding to the performance of resources of nodes 115. Performanceof resources of nodes 115 may include any suitable performance metric,such as response times, proportion of successfully executed operations,consumptions, or utilizations. Data related to the performance of aresource may include values representing a measure of a particularperformance metric. For example, synthetic application modules 215 maybe configured to commence measuring a time duration upon an eventinitiating a resource consumption. Synthetic application modules 215 maybe configured to cease measuring a time duration upon an eventterminating a resource consumption. Synthetic application modules 215may be configured to measure a time duration between issuing a resourceconsumption request to another instance of synthetic application 130 andreceiving a reply. Analysis of data relating to the performance of aresource may indicate the suitability of nodes 115 for hostingparticular real world applications with resource consumptions similar toresource consumptions of synthetic applications 130.

In some embodiments, data collected by synthetic application module 215may be stored in memory 210 and/or storage 220. Memory 210 and/orstorage 220 may include a database, directory, or other data structureoperable to store data. Further, memory 210 and/or storage 220 mayinclude any instrumentality or aggregation of instrumentalities that mayretain data and/or instructions for a period of time. Storage 220 mayinclude random access memory (RAM), electrically erasable programmableread-only memory (EEPROM), a Personal Computer Memory Card InternationalAssociation (PCMCIA) card, flash memory, solid state disks, hard diskdrives, magnetic tape libraries, optical disk drives, magneto-opticaldisk drives, compact disk drives, compact disk arrays, disk arraycontrollers, and/or any suitable selection or array of volatile ornon-volatile memory operable to store data. Performance data consistingof, for example, time durations of resource consumption may be stored inan array, a database, a matrix, or any other suitable data structure forstoring performance data.

In some embodiments, synthetic application modules 130 or nodes 115 maybe configured to communicate with other synthetic application modules103 or nodes 115 using network interface 230. Network interface 230 mayinclude any adapter or hardware operable to communicate using network120, such as hardware or circuitry for connecting to network connectionsuch as Fibre Channel, Frame Relay, Asynchronous Transfer Mode (ATM),Internet protocol (IP), other packet-based protocol, small computersystem interface (SCSI), Internet SCSI (iSCSI), advanced technologyattachment (ATA), serial ATA (SATA), advanced technology attachmentpacket interface (ATAPI), serial storage architecture (SSA), integrateddrive electronics (IDE), and/or any combination thereof.

Each synthetic application 130 may be implemented in any suitableportion of node 115. Although each node 115 is illustrated as containinga synthetic application 130, in various embodiments syntheticapplication 130 may be implemented in only a portion of nodes 115.Furthermore, in various other embodiments, multiple instances ofsynthetic application 130 may be implemented in various ones of nodes115. Instances of synthetic application 130 may be communicativelycoupled to other instances of synthetic application 130 via network 120.

FIG. 3 is an illustration of synthetic application definition 225, inaccordance with the teachings of the present disclosure. Syntheticapplication modules 215 may be configured to consume different resourcesor groups of resources of nodes 115 based upon synthetic applicationdefinition 225, as shown in FIG. 3.

Synthetic application definition 225 may include registry 305. Registry305 may include one or more lists 310 of nodes 115 in system 100. Lists310 may include references to all nodes 115 in system 100 or to a subsetof all nodes 115. For example, list 310 may include references to onlythose nodes 115 described in instances of business functions 355. Inaddition to list 310, registry 305 may also include addresses 315.Addresses 315 may correspond to, for example, nodes 115 or instances ofsynthetic application 130. For example, addresses 315 may any includeany suitable address, such as an internet protocol (IP) address.

Synthetic application definition 225 may also include one more workloads320. Workloads 320 may include any suitable number or kind of parameters325 specifying the operation of synthetic application 130. Parameters325 may have corresponding values 330.

In some embodiments, an instance of synthetic application 130 may beconfigured as a supervisor instance. Supervisor instances of syntheticapplication 130 may control the configuration of others instances ofsynthetic applications 130. In other embodiments, an instance ofsynthetic application 130 may be configured as a master instance. Masterinstances of synthetic application 130 may initiate resourceconsumptions based upon workloads 320. In some embodiments, masterinstances of synthetic applications 130 may be configured to implementthe functionality of master instances, supervisor instances, or acombination of the two. In other embodiments, supervisor instances ofsynthetic applications 130 may be configured to implement thefunctionality of master instances, supervisor instances, or acombination of the two.

Synthetic application 130 may be configured to implement businessfunctions 355 one or more times. Thus, parameters 325 of workload 320may include a number of iterations to implement business functions 355.Such a parameter may include, for example, WorkloadIterations 370.Values 330 associated with this parameter may include any suitablerepresentation of a number of iterations, such as an integral number.

Iterations of business functions 355 may be temporally spaced apart fromeach other by a delay. Thus, workload 320 may include parameters 325specifying a delay between consecutive iterations of syntheticapplication 130. Such a parameter may include, for example,WorkloadDelay 375. Values 330 associated with this parameter may includeany suitable representation of a delay period, such as time durations,or duration of execution of a set of computer-program instructions.

Workload 320 may include a parameter specifying a payload size ofsynthetic application 130. Such a parameter may include, for exampleWorkloadReqSize 380. Synthetic application definitions may specify oneor more instances of synthetic application 130 configured toautonomously initiate resource consumptions based on workloads 320. Suchinstances of synthetic application 130 may be referred to as masterinstances.

Master instances of synthetic applications 130 may initiate resourceconsumptions by transmitting data via network 120 to one or more otherinstances of synthetic application 130. In some embodiments, transmitteddata may include requests for resource consumptions. In otherembodiments, transmitted data may additionally include payload data.Payload data may include segments of data to be transmitted to anotherinstance of synthetic application 130. Associated values 330 maydescribe any suitable measure of sizes of payloads to be transmitted vianetwork 120, such as numbers of bytes.

Synthetic application 130 may be configured to perform only oneiteration at a time, or, alternatively, may be configured to perform oneor more iterations in parallel. Workload 320 may include a parameter 325specifying the maximum number of iterations of synthetic application 130that can be performed concurrently. Such a parameter may include, forexample, WorkloadConcurrency 385. Concurrency may also be referred to asthe degree of parallelism of synthetic application 130. Values 330 ofthis parameter may include any suitable value for specifying a degree ofparallelism, such as an integral number.

If synthetic application 130 is configured to effectuate more than oneconcurrent iteration, workload 320 may additionally include a parameter325 such as WorkLoadKind 390, describing whether iterations of syntheticapplication 130 may be executed synchronously or asynchronously. Ifiterations of synthetic application 130 may be executed synchronously,synthetic application 130 may be configured to wait for an iteration ofresource consumptions initiated by synthetic application 130 to completebefore launching a subsequent iteration of synthetic application 130. Ifsynthetic application 130 may be executed asynchronously, syntheticapplication 130 may be configured to launch a subsequent iteration ofsynthetic application 130 before a previous iteration of syntheticapplication 130 has completed. Values 330 of this parameter may beinclude any suitable representation of whether synthetic application 130is to be executed synchronously or asynchronously, such as a Booleanvalue, or a string. In some embodiments, a particular workload may bedefined to operate synchronously. In other embodiments a workload may bedefined to operate asynchronously. In further embodiments, a portion ofa workload may be defined to operate synchronously, while a differentportion of the workload may be defined to operate asynchronously.

Synthetic application 130 may be configured to effectuate any number ofiterations of one or more business functions 355. In some embodiments,if synthetic application definition 225 specifies multiple iterations ofmore than one business function 355, iterations may be allocated equallybetween instances of business functions 355. In other embodiments,workload 320 may include a mix 335 of business functions 355. Mix 355may include mix parameters 340 and mix values 345. Mix parameters 340may describe proportions of iterations to be allocated to particularbusiness functions 355. Instances of mix parameters 340 may referenceparticular business functions 355. Mix values 345 may include anysuitable description of a proportion of iterations to be allocated toparticular instances of business functions 355, such as a fraction, apercentage, a count.

Workload 320 may also include any other suitable parameter specifyingthe operation of synthetic application 130.

In some embodiments of the present disclosure, synthetic applicationdefinition 225 may enumerate one or more business functions 355.Business functions 355 may include sequences of resource consumptions ofnodes 115 of system 100. Business functions 355 may, for example,describe sequences of resources of one or more nodes 115 to be consumedby synthetic application 130. Resources of particular nodes 115 may beincluded in one or more business functions 355. Further, resources ofparticular nodes 115 may be included one or more times within particularbusiness functions 355. Business functions 355 may include associatednode properties 360 for one or more nodes 115 included in sequences ofresource consumptions.

Business functions 355 may describe a hierarchical sequence of resourceconsumptions across multiple instances of synthetic application 130.Business functions 355 may specify that various instances of syntheticapplication 130 initiate resource consumptions in response to initiatingevents. For example, business functions 355 may specify one or moreinstances of synthetic application 130 configured to initiate resourceconsumptions autonomously based on workloads 320. Such instances ofsynthetic application 130 may be referred to as master instances. Amaster instance may control the configuration of others instances ofsynthetic application 130. In other embodiments, instances of syntheticapplications 130 may be configured to initiate resource consumptions ofnodes 115 described in business functions 355 upon any other suitableinitiating event, such as receipt of a request from another instance ofsynthetic application 130. Requests may include any suitable forms ofrequests, such as a data transmission via network 120.

For example, business functions 355 may describe initiating resourceconsumptions of nodes 115 based upon resource consumption of network 120connected to an instance of synthetic application 130 within nodes 115.A particular instance of synthetic application 130 configured to send aninitiating event to another instance of synthetic application 130 may bereferred to as a parent. An instance of synthetic application 130configured to initiate resource consumptions of nodes 115 based uponreceipt of an initiating event may be referred to as a child. Instancesof synthetic application 130 configured as children may send replies toinstances of synthetic application 130 configured as parents afterconsuming resources of nodes 115 as described in business functions 355.Replies may include any suitable forms of replies, such as a datatransmission via network 120.

One type of resource consumption described in business functions 355 mayspecify that, upon receiving a request from another instance ofsynthetic application 130 configured as a parent, an instance ofsynthetic application 130 in a particular node 115 may send one or morerequests to other instances of synthetic applications 130. Thus, asingle instance of synthetic application 130 may be configured as both aparent and a child depending on the context of the request/replyrelationship with other instances of synthetic application 130.

For example, exemplary business function 355A may include instances ofsynthetic application 380A, 380B, and 380C, each with associated nodeproperties 360A, 360B, and 360C, respectively. Exemplary businessfunction 355A may begin, based upon workload 320, with syntheticapplication 380A consuming resources of an associated node 115,according to node properties 360A. Business function 355A may furtherspecify that synthetic application 380A, after consuming resources ofassociated node 115, send request 381 to synthetic application 380B.Exemplary business function 355A may further specify that syntheticapplication 380B consume resources of an associated node 115, accordingto node properties 360B. Business function 355A may further specify thatsynthetic application 380B, after consuming resources of associated node115, send request 382 to synthetic application 380C. Exemplary businessfunction 355A may further specify that synthetic application 380Cconsume resources of an associated node 115, according to nodeproperties 360C. Business function 355A may further specify thatsynthetic application 380C, after consuming resources of associated node115, send reply 383 to synthetic application 380B. Business function355A may further specify that synthetic application 380B, afterconsuming resources of associated node 115, send reply 384 to syntheticapplication 380A.

Exemplary business function 355B may include instances of syntheticapplication 380D and 380E, each with associated node properties 360D and360E, respectively. Exemplary business function 355B may begin, basedupon workload 320, with synthetic application 380D consuming resourcesof an associated node 115, according to node properties 360D. Businessfunction 355B may further specify that synthetic application 380D, afterconsuming resources of associated node 115, send request 385 tosynthetic application 380E. Exemplary business function 355B may furtherspecify that synthetic application 380E consume resources of anassociated node 115, according to node properties 360E. Businessfunction 355B may further specify that synthetic application 380E, afterconsuming resources of associated node 115, send request 386 tosynthetic application 380D. Exemplary business function 355B may furtherspecify that synthetic application 380D consume resources of anassociated node 115, according to node properties 360D. Businessfunction 355B may further specify that synthetic application 380D, afterconsuming resources of associated node 115, send reply 387 to syntheticapplication 380E. Business function 355B may further specify thatsynthetic application 380E, after consuming resources of associated node115, send reply 388 to synthetic application 380D.

In some embodiments of the present disclosure, synthetic applicationdefinition 225 may include default parameters 365. If one or moreparameters of an instance of node properties 360 of syntheticapplication definition 225 do not have an assigned value, parameters maybe assigned values with reference to default parameters 365. Defaultparameters 365 may include, for example, some or all of the parametersincluded in node properties 360. Parameters of node properties 360, suchas parameters 402 may be assigned values 404, based upon defaultparameters values 375. A particular instance of synthetic applicationdefinition 225 may have different default parameters 365 than anotherinstance of synthetic application definition 225.

FIG. 4 is an illustration of node properties 360, in accordance with theteachings of the present disclosure. Node properties 360, as shown inFIG. 4 may describe resource consumptions of nodes 115. Such resourceconsumptions may include, but are not limited to, processing resources,memory resources, storage resources, network resources, and otherresources related to infrastructure assets that can be described interms of quantity and/or rate and/or usage of components nodes 115. Insome embodiments of the present disclosure, resource consumptions mayinclude, for example, sending data between nodes 115 via network 120,executing computer program instructions on a computer processor, writingand/or reading to and/or from a storage device, writing and/or readingto or from a memory, or any other suitable resource consumption orcombination of resource consumptions. Where a single resource isreferenced, it may be understood that multiple resources may beconsumed. Node properties 360 may include consumption parameters 402with associated consumption values 404.

Node properties 360 may include parameters describing protocols forconsuming of resources of nodes 115 in response to multiple initiatingevents. For example, node properties 360 may include properties such asThreadLimit 406. ThreadLimit 406 may describe a maximum number of groupsof resource consumptions that synthetic application 130 can effectuateconcurrently, wherein each group of resource consumptions is responsiveto a particular initiating event. If more than one concurrent operationis described in ThreadLimit 406, synthetic application 130 may consumeresources of nodes 115 based upon multiple initiating eventsconcurrently. If synthetic application 130 is configured by ThreadLimit406 to effectuate only a single concurrent operation, resourceconsumptions responsive to a first initiating event must be completedbefore commencing resource consumptions responsive to a subsequentinitiating event. Associated consumption values 404 may describe anysuitable representation of a maximum number of concurrent consumptions,such as an integral number.

Node properties 360 may describe a number requests for resourceconsumptions to be sent by an instance of synthetic application 130configured as a parent to an instance of synthetic application 130configured as a child. In some embodiments, after consuming resources ofa node 115, synthetic application 130 may send a single request toanother instance of synthetic application 130 configured as a child vianetwork 120. In other embodiments, synthetic application 130 may sendmore than one request to another instance of synthetic application 130configured as a child via network 120. Node properties 360 may includeconsumption parameters 402, such as FanOuts 408, describing numbers ofrequests to be sent. Associated consumption values 404 may describenumber of requests in any suitable format, such as an integral number,

Node properties 360 may also describe proportions of temporal overlapbetween multiple types of resource consumptions responsive to a singleinitiating event. Node properties 360 may include consumption parameters402, such as SerialExecution 410, describing proportions of temporaloverlap between different types of resource consumptions. For example,node properties 360 may describe consuming storage resources of nodes115 and processor resources of nodes 115. If, for example, consumptionvalues 404 associated with SerialExecution 410 describe no permissibletemporal overlap, storage resource consumptions may be completed beforesynthetic application 130 begins consuming processor resources of node115, or vice versa. In other embodiments, if consumption values 404associated with SerialExecution 410 describe permissible temporaloverlap, storage resource consumptions may effectuated concurrently, orpartially concurrently, with processor resource consumptions of node115. Associated consumption values 404 may include any other suitabledescription of a proportion temporal overlap between resourceconsumptions of nodes 115, such as fractions, percentages, counts,binary values, or Boolean statements.

Node properties 360 may describe consumption of storage resources ofnodes 115. In some embodiments of the present disclosure, resourceconsumptions may include sequences of read and write operations tostorage resources of one or more nodes 115. Consumptions of storageresources may be described in terms of number, size, and/or frequency ofread and write operations to or from storage devices of nodes 115. Nodeproperties 360 may include consumption parameters 402, such as ReadBytes412, describing various sizes of such operations. Associated consumptionvalues 404 may describe any suitable measure of storage consumptions,such as a size of such operations in a number of bytes to be read fromand/or written to a storage device. Further, node properties 360 maydescribe effectuating a read and/or write operation one time or multipletimes. Node properties 360 may contain parameters 402, such as ReadLoops414, describing a number of times to effectuate such operations.Associated consumption values 404 may describe any suitable measure ofnumbers of times to repeat storage consumptions, such as a count ofoperations in an integral number of repetitions.

In some embodiments of the present disclosure, node properties 360 maydescribe consumption of processing resources of nodes 115. Syntheticapplication 130 may effectuate processing resource consumptions bycausing nodes 115 to execute computer program instructions. Resourceconsumptions of processing resources of nodes 115 may be described inplatform independent measurements of consumption, such as totalprocessing power. Node properties 360 may include consumption parameters402, such as CPUConsume 412, describing various sizes of suchoperations. In some embodiments, synthetic application modules 215 maybe configured to generate computer executable program code, customizedfor a particular node 115, that consumes a platform-independent amountof resources.

In some embodiments, to consume an amount of processing resources of anode 115, synthetic application module 215 may generate program code toexecute one or more loops of a set of computer-program instructions.Each loop may perform instances of a variety of typical processingresource consumptions, such as floating point calculations, Fibonaccicalculations, sorting tasks, “card shuffling” tasks, data compressionand decompression tasks, prime number calculations, sequence searching,or any other suitable type of processing resource consumption. Each typeof processing resource consumption may have an associated weighting sothat more, fewer, or equal processing resources are consumed for thattype of processing resource consumption per loop as compared to othertypes. In some embodiments, weightings associated with types ofprocessing resource consumptions may be the same for each node 115. Inother embodiments, weightings associated with types of processingresource consumptions for different nodes 115 may be adjusted based on ahardware configuration of a particular node 115, an expected behavior ofa real-world application, or any other suitable characteristic foradjusting weightings.

Node properties 360 may contain parameters 402, such as CPUConsume 412,describing an amount of processing resource to be consumed. Associatedconsumption values 404 may describe any suitable measure of processingresource consumptions. In some embodiments, associated consumptionvalues 404 may describe a number of loops to be executed. In otherembodiments, associated consumption values 404 may describe a period oftime during which loops should be executed continuously. In furtherembodiments, associated consumption values 404 may describe a rate ofloops to be executed per time period.

Node properties 360 may describe consumption of resources of network 120connecting two or more nodes 115. For example, business functions 355may specify instances of synthetic application 130 configured as parentsto cause nodes 115 to transmit data via network 120 to one or moreinstances of synthetic application 130 configured as children. Nodeproperties 360 may include consumption parameters 402, such as ReqSizes418, describing various sizes of such transmitted data. Associatedconsumption values 404 may describe any suitable measure of sizes ofdata to be transmitted via network 120, such as numbers of bytes.Instances of synthetic application 130 configured as children maytransmit replies to instances of synthetic application 130 configured asparents by transmitting data, as specified in business functions 355.Node properties 360 may include consumption parameters 402, such asReplyBytes 420, describing various sizes of such transmitted data.Associated consumption values 404 may describe any suitable sizes ofdata to be transmitted via network 120, such as numbers of bytes.Although instances of synthetic application 130 configured as childrenor parents are described, network transmissions defined by nodeproperties 360 may be performed between any suitable ones of nodes 115.

Node properties 360 may describe consumption of memory resources ofnodes 115. Memory resources may be consumed by allocating blocks ofmemory of nodes 115. Upon receipt of an initiating event, syntheticapplication 130 may reserve a segment of memory of nodes 115. Nodeproperties 360 may include consumption parameters 402, such asReqMemBytes 422, describing various sizes of such segments. Associatedconsumption values 404 may describe any suitable measure of memorysegments, such as sizes of such segments in numbers of bytes to bereserved in memory. Upon beginning execution of a business function,synthetic application 130 may also reserve a segment of memory of nodes115. Node properties 360 may include consumption parameters 402, such asBFMemBytes 423, describing various sizes of such segments. Associatedconsumption values 404 may describe any suitable measure of memorysegments, such as sizes of such segments in numbers of bytes to bereserved in memory. Synthetic application 130 may further reservesegments of memory independent of any initiating events. Node properties360 may include consumption parameters 402, such as AppMemBytes 424,describing various sizes of such segments. Associated consumption values404 may describe any suitable measure of memory segments, such as sizesof such segments in numbers of bytes to be reserved in memory.

Node properties 360 may specify a maximum number of requests to otherinstances of synthetic application 130 configured as children that maybe concurrently outstanding. In some embodiments, numbers ofconcurrently pending requests may be monitored with reference to apopulation of tokens. For example, particular tokens may be reserved bysynthetic application modules 215 for each request made instances ofsynthetic application 130 configured as a child. Upon receiving a reply,synthetic application modules 215 may release tokens corresponding tothe original request. Node properties may include a parameter specifyinga number of tokens, such as Tokens 426. Associated consumption values404 may describe any suitable descriptions of token populations, such asstrings, or numbers.

Real-world applications may consume resources in time varyingmagnitudes. For example, sizes of data transfers may vary betweentransfers. Likewise, size and frequencies of read and/or writeoperations to a storage device may vary between operations. Nodeproperties 360 may describe resource consumptions in terms ofdistributions of resource consumptions, rather than a single value of aresource consumption. Where a value of a parameter of node properties360 is referenced, it may be understood that a distribution of valuesmay also be referenced. For example, values of parameters of nodeproperties 360 may describe any suitable distribution of values, such asa uniform distribution, gamma distribution, Poisson distribution, adefined table, or a normal distribution.

Node properties 360 may also include parent node 428. Parent node 428may include any suitable reference to a node 115 of system 100. Parentnode 428 may have an associated address 430. After resource consumptionof a node 115 are effectuated by an instance of synthetic application130, synthetic application 130 may send a reply to parent node 428. Areply may be sent via network 120, for example, and may be addressed toparent node 428 by reference to address 430. Address 430 may include anysuitable address for parent node 428, such as an internet protocol (IP)address.

Node properties 360 may also include one or more child flows 455. Childflows 455 may include information derived from business functions 355 ofsynthetic application definition 225. Child flows 455 may describeinstances of synthetic applications 480 configured as children of aninstance of synthetic application 130 to be configured according to nodeproperties 360. Child flows 455 may include node properties 460associated with instances of synthetic applications 480 configured aschildren. Child flows 455 may further describe one or more requests 482to be made to child synthetic application 482 and one or more replies483 to be made to back to an instance of synthetic application 130 to beconfigured according to node properties 360.

FIG. 5 is an illustration of the operation of system 500 for performingapplication-specific assessment of cloud hosting suitability, inaccordance with the teachings of the present disclosure. System 500 mayinclude nodes 502, 504, 506, and 508. Nodes 502, 504, 506, 508 may beimplemented by any suitable node, such as those illustrated in FIG. 1.Although a particular number and arrangement of nodes is illustrated inFIG. 5, any suitable number, combination, arrangement, or topology ofnodes may be used, such as a loop, ring, bus, star, point-to-point,mesh, or daisy-chain. Such topologies may be physical or virtual.

In some embodiments of the present disclosure, synthetic application 530may be initiated by introducing synthetic application definition 525 tosystem 500. For example, synthetic application definition 525 may beintroduced to system 500 by a file transfer protocol, hyper-texttransfer protocol, manual loading from a universal serial bus (USB)storage device, or any other suitable means of introducing syntheticapplication definition 525 to system 500. In particular, syntheticapplication definition 525 may be introduced to one or more instances ofsynthetic applications within one or more nodes of system 500. Aninstance of a synthetic application to which a synthetic applicationdefinition is introduced may be referred to as a master instance. Forexample, synthetic application definition 525 may be introduced tosynthetic application 530 in node 502. Thus, synthetic application 530is a master instance. Master instances of synthetic applications mayinitiate resource consumptions autonomously based on workloads withinsynthetic application definitions, rather than initiating resourceconsumptions in response to an initiating event from a parent node.

Synthetic application modules may parse the components of syntheticapplication definitions. For example, synthetic application module 515within node 502 may analyze a registry of synthetic applicationdefinition 525. Synthetic application module 515 may analyze a registryof synthetic application definition 525 by, for example, reading a listof instances of synthetic applications within the registry. Syntheticapplication module 515 may further analyze a registry of syntheticapplication definition 525 by, for example, reading a list of address ofinstances of synthetic applications within the registry and associatingaddresses with instances of synthetic applications.

Synthetic application modules may further parse synthetic applicationdefinitions by analyzing one or more business functions in syntheticapplication definition files. For example, synthetic application module525 may analyze business functions in synthetic application definition525. Analysis of business functions may include identifying instances ofsynthetic applications, described in business function, which willconsume resources of various nodes of the system. By way of example,synthetic application definition 502 may include multiple businessfunctions. For example, business function 598 might define node 504 as achild of node 502, and node 506 as a child of node 508. Businessfunction 599 might define node 508 as a child of node 502, and node 502as a child of node 508.

Instances of synthetic applications within nodes described by businessfunctions may be identified. For example, synthetic application 530 mayparse business function 598 and identify synthetic applications 531 and532. Additionally, synthetic application 530 may parse business function599 and identify synthetic applications 530 and 533.

Synthetic application modules may further parse synthetic applicationdefinitions by analyzing instances of node properties within businessfunctions. Analysis of instances of node properties may includeidentifying parameters of node properties with no associated values.Values may be supplied for such parameters by reference to defaultparameters of synthetic application definition. For example, syntheticapplication module 515 may analyze node properties 560 of syntheticapplication definition 525.

After parsing synthetic application definitions, synthetic applicationmodules may be configured to automatically transmit node properties tonodes identified by synthetic application module as included in businessfunctions of synthetic application definition. Node properties may betransmitted via a network or any other suitable means. In oneembodiment, based upon business function 598, synthetic application 530may transmit node properties 561 to synthetic application 531 in node504. Further, based upon business function 598, synthetic application530 may transmit node properties 562 to synthetic application 532 innode 506, at 501. In another embodiment, based upon business function598, synthetic application 530 may transmit node properties 561 tosynthetic application 531 in node 504, at 503. Based upon businessfunction 598, synthetic application 531 may transmit node properties 562to synthetic application 532 in node 506, at 505. Likewise, based uponbusiness function 599, synthetic application 530 may transmit nodeproperties 563 to synthetic application 533 in node 508, at 507.

After synthetic application modules have distributed node properties tonodes described in business functions of synthetic applicationdefinitions, synthetic application modules may initiating resourceconsumptions based upon workloads of synthetic application definitions.For example, based upon business function 598, synthetic application 530may consume resources of node 502 based upon a workload in syntheticapplication definition 525. For example, based upon parameters in nodeproperties file 560, synthetic application 530 may: send instructions571 to processor 535 to consume processing resources; send instructions573 to memory 540 to consume memory resources; and send instructions 575to consume storage resources 545. After resource consumptions of node502 are complete, synthetic application 530 in node 502 may initiate arequest 509 to synthetic application module 531 in node 504. Request 509may include any suitable request, such as a data transfer via a network.Upon receipt of request 509, synthetic application 531 may consumeresources of node 504. For example, based upon parameters in nodeproperties file 561, synthetic application 531 may: send instructions577 to processor 536 to consume processing resources; send instructions579 to memory 541 to consume memory resources; and send instructions 581to consume storage resources 547. After resource consumptions of node504 are complete, synthetic application 531 may send one or morerequests 511 to synthetic application 532 in node 506 as described inbusiness function 598.

Request 511 may be any suitable request, such as a data transfer via anetwork. Upon receipt of request 511, synthetic application 532 mayconsume resources of node 506. For example, based upon parameters innode properties file 562, synthetic application 532 may: sendinstructions 583 to processor 537 to consume processing resources; sendinstructions 585 to memory 542 to consume memory resources; and sendinstructions 587 to consume storage resources 547. After resourceconsumptions of node 506 are complete, synthetic application 532 maysend one or more replies 512 to synthetic application 531 in node 504 asdescribed in business function 598. Upon receipt of reply 512, syntheticapplication 531 may send one or more replies 510 to syntheticapplication 530 in node 502 as described in business function 598. Uponreceipt of replies 510, one iteration of exemplary business function 598may be complete. Synthetic application 515 may be configured to measurea time duration between initiating resource consumption of node 502 andreceipt of reply 520. Time durations between requests and replies may bestored in storage associated with synthetic application 530.

Based upon business function 599, synthetic application 530 may againconsume resources of node 502 based upon a workload in syntheticapplication definition 525. For example, based upon parameters in nodeproperties file 560, synthetic application 530 may: send instructions571 to processor 535 to consume processing resources; send instructions573 to memory 540 to consume memory resources; and send instructions 575to consume storage resources 545. After resource consumptions of node502 are complete, synthetic application 530 in node 502 may initiate arequest 513 to synthetic application module 533 in node 508. Request 513may be any suitable request, such as a data transfer via a network. Uponreceipt of request 513, synthetic application 533 may consume resourcesof node 508. For example, based upon parameters in node properties file563, synthetic application 533 may: send instructions 589 to processor538 to consume processing resources; send instructions 591 to memory 54to consume memory resources; and send instructions 593 to consumestorage resources 548. After resource consumptions of node 508 arecomplete, synthetic application 533 may send one or more requests 514 tosynthetic application 530 in node 502 as described in business function599.

Request 513 may be any suitable request, such as a data transfer via anetwork. Upon receipt of request 513, synthetic application 530 mayconsume resources of node 502. For example, based upon parameters innode properties file 560, synthetic application 530 may: sendinstructions 571 to processor 535 to consume processing resources; sendinstructions 573 to memory 540 to consume memory resources; and sendinstructions 575 to consume storage resources 545. After resourceconsumptions of node 502 are complete, synthetic application 530 maysend one or more replies 519 to synthetic application 533 in node 506 asdescribed in business function 599. Upon receipt of replies 519,synthetic application 533 may send one or more replies 520 to syntheticapplication 530 in node 502 as described in business function 599. Uponreceipt of replies 520, one iteration of exemplary business function 599may be complete. Synthetic application 515 may be configured to measurea time duration between initiating resource consumption of node 502receipt of replies 520. Time durations between requests and replies maybe stored in storage associated with synthetic application 530.

FIG. 6 is a flowchart of an exemplary method 600 for performingapplication-specific assessment of cloud hosting suitability, inaccordance with the teachings of the present disclosure. Although FIG. 6discloses a particular number of steps to be taken with respect toexemplary method 600, method 600 may be executed with more or fewersteps than those depicted in FIG. 6. In addition, although FIG. 6discloses a certain order of steps to be taken with respect to method600, the steps of these methods may be completed in any suitable order.Method 600 may be implemented using the system of FIGS. 1-5, 7, 9, 11,13, or any other suitable mechanism. In certain embodiments, method 600may be implemented partially or fully in software embodied incomputer-readable storage media.

Program instructions may be used to cause a general-purpose orspecial-purpose processing system that is programmed with theinstructions to perform the operations described below. The operationsmay be performed by specific hardware components that contain hardwiredlogic for performing the operations, or by any combination of programmedcomputer components and custom hardware components. Method 600 may beprovided as a computer program product that may include one or moremachine readable media having stored thereon instructions that may beused to program a processing system or other electronic device toperform the methods.

In some embodiments, method 600 may begin at step 605. At step 605, asynthetic application may be deployed to various nodes of a computingsystem, for example computing system 100 of FIG. 1, or system 500 ofFIG. 5. Nodes may include, for example, a server (e.g., blade server orrack server), personal computer (e.g., desktop or laptop), tabletcomputer, mobile device (e.g., personal digital assistant (PDA) or smartphone), network storage device, printer, switch, router, data collectiondevice, virtual machine, script, executable, firmware, library, sharedlibrary, function, module, software application, or any other suitabledevice or application. Synthetic applications may be deployed to nodesby use of a network or any other suitable means of deploying syntheticapplications.

At step 610, synthetic application definitions may be introduced to oneor more synthetic applications of nodes of a computing system, forexample synthetic application definition 225 of FIG. 3. Syntheticapplication definitions may be distributed to nodes by use of a networkor any other suitable means of deploying synthetic applicationdefinition. An instance of synthetic application to which a syntheticapplication definition is distributed may be referred to as a masterinstance of synthetic application.

At step 615, synthetic application modules of a synthetic applicationmay parse a registry of a synthetic application definition, for example,registry 305 of FIG. 3. A registry may include listings of nodesdescribed in synthetic application definition. A registry may furtherinclude addresses of corresponding to nodes described in a registry.Addresses may include, for example, internet protocol addresses, or anyother suitable type of address.

At step 620, synthetic application modules of a synthetic applicationmay parse business functions of a synthetic application definition, forexample, business functions 355A and 355B of FIG. 3. Parsing businessfunctions of synthetic application definitions may include identifyingother instances of synthetic applications described in businessfunctions. For example, as shown in FIG. 3, synthetic application modulemay identify instances of synthetic applications such as 380A, 380B,380C, 380D and/or 380E.

At step 625, synthetic application modules may parse node properties ofsynthetic application definition, for example node properties 360 ofFIG. 4. Parsing node properties may include reading child flows of nodeproperties, for example, child flows 455A of FIG. 4. Parsing nodeproperties may further include identifying a parent node, such as parentnode 428 of FIG. 4, and an associated address, such as address 430 ofFIG. 4.

At step 630, synthetic application modules may determine whether nodeproperties have values associated with parameters of node properties,for example values 404 of parameters 402 as show in FIG. 4. If one ormore instances of node properties do not have values associated withparameters, at step 635, synthetic application modules may refer todefault parameters, such as default parameters 365 of FIG. 3, to supplyparameter values. The method may proceed to step 640.

After node properties have values for parameters, at step 640, syntheticapplication modules may distribute node properties to other instances ofsynthetic application modules. For example, node properties may bedistributed to one or more instances of synthetic application describedin child flows of node properties. Node properties may be distributed toinstances of synthetic applications via a network or any other suitablemeans of distribution.

At step 645, if a synthetic application is configured as a masterinstance, the method may proceed to step 650. If a synthetic applicationis not configured as a master instance, the method may proceed to step670.

At step 650, a synthetic application configured as a master instance mayinitiate resources consumptions based upon one or more workloads. Forexample, synthetic application modules may commence consuming resourcesof a computing system. Consumption of resources may begin, for example,by one or more master instances of synthetic application issuingresource consumption requests according to workloads in syntheticapplications definitions. Issuing consumption requests may also includebeginning data collection of time durations between requests andreplies.

At step 655, instances of synthetic applications configured as masterinstances may wait for replies from instances of synthetic applicationconfigured as children. For example, replies may include a transmissionof data over a network from an instance of a synthetic applicationconfigured as a child. Replies from instances of synthetic applicationsconfigured as children may be sent after those instances have completedresource consumptions, such as in step 685.

At step 660, an instance of a synthetic application configured as amaster instance may record results. Recording results may include, forexample, recording time durations between issuing requests and receivingreplies. Results may be stored in a storage resource of a nodeassociated with an instance of a synthetic application, or any othersuitable storage resource.

At step 665, synthetic application modules may determine whethersufficient results have been collected. Such a determination may bebased upon statistical analysis, other industry best practices, or anyother suitable method. If sufficient results have been collected, themethod may proceed to step 690. Otherwise, the method may return to step650.

If, at step 645, an instance of a synthetic application is notconfigured as a master instance, the method may proceed to step 670. Atstep 670, an instance of a synthetic application may wait for a requestfrom a parent node, such as a request from step 650, or a request fromstep 680. Upon receipt of such a request, the method may proceed to step675.

At step 675, instances of synthetic application modules may consumeresources of nodes of a computing system. For example, syntheticapplication modules may consume processing resources, storage resources,memory resources, network resources, and/or any other suitable resourceassociated with nodes of a computing system. Resource consumption may beeffectuated based upon parameters included in node properties.

At step 680, instances of synthetic applications may interact with otherinstances of synthetic applications configured as children. Interactionsmay include sending requests, wait for replies, receiving replies orrecording results.

At step 685, instances of synthetic applications configured as childrenmay send replies to instances of synthetic applications configured asparents. Replies may include transmissions of data to a parent node overa network. Replies may also include recorded result data frominteractions with child nodes.

At step 690, results may be evaluated. For example, time duration datacorresponding to instances of synthetic applications may be compared tothreshold performance requirements. Any suitable method of evaluatingtime duration data may be used. Method 600 may repeat with differentsynthetic applications or different synthetic application definitions,or may terminate.

FIGS. 7A and 7B are illustrations of an exemplary system 700 forperforming application-specific assessment of cloud hosting suitabilityfor multiple applications, in accordance with teachings of the presentdisclosure. System 700, as shown in FIGS. 7A and 7B, may includeinstances of synthetic applications configured to consume resources ofnodes of system 700 based on multiple synthetic application definitions.For example, system 700 may be configured to effectuate multipleresource consumptions of nodes in cloud 702. Cloud 702 may include nodes712, 714, and 716. Nodes 712, 714, and 716 may include syntheticapplications 718, 720, and 722, respectively.

In some embodiments, synthetic applications may be configured toeffectuate resource consumptions based upon two or more relatedinstances of synthetic application definitions. For example, an instanceof a synthetic application definition may describe resource consumptionsof a particular real-world application based upon a particular level ofuser demand. However, an operator of such a real-world application maypredict that level of user demand may change. Thus, an additionalinstance of synthetic application definition may be created, wherein theadditional synthetic application definition describes predicted resourceconsumptions of a real-world application based upon a different level ofuser demand.

Additional instances of synthetic application definitions may be createdby modifying one or more values associated with resource consumptions ina first synthetic application definition. For example, an additionalinstance of a synthetic application definition may be created from afirst synthetic application by any suitable means, including but notlimited to: multiplying one or more values by a scaling factor, addingan offset to one or more values, altering the mix of business functionsaltering business functions, altering workloads, or alerting nodeproperties.

In one embodiment, synthetic applications 718, 720, 722 may beconfigured to illustrate whether cloud 702 may accommodate increasedchanges in application footprint in resource consumption. In anotherembodiment, synthetic applications 718, 720, 722 may be configured todetermine whether resources, up-time, or availability of cloud 702 maybe reduced while still meeting performance goals. In yet anotherembodiment, synthetic applications 718, 720, 722 may be configured todetermine whether cloud 702 may increase resources of existing nodes712, 714, 716 or add further nodes to meet performance goals.

Evaluation of increased changes in application footprint in resourceconsumption, performance goals, or other execution metrics of cloud 702may be performed in any suitable manner. In one embodiment, evaluationof execution may be made by measuring response time for a given businessfunction or other operation to be executed by synthetic applications718, 720, 722. Response time may include time required to propagateinformation between synthetic applications 718, 720, 722 as well as timerequired for each synthetic application 718, 720, 722 to performspecified tasks.

As shown in FIG. 7A, synthetic application definition 704 may beintroduced to synthetic application 718. Synthetic application 718 mayparse synthetic application definition 704. Synthetic application 718may distribute node properties 782A and 782B to synthetic application720 in node 714, and synthetic application 722 in node 716,respectively. Once nodes described in business functions of syntheticapplication definition 704 have node properties 782, syntheticapplication 718 may send one or more requests 750 to syntheticapplication 720. Synthetic application 718 may begin measuring timedurations for instances of requests 750. Responsive to such requests,synthetic application 720 may initiate resource consumptions of node714. Based upon business functions in synthetic application definition704, synthetic application 720 may send one or more requests 752 tosynthetic application 722. Synthetic application 720 may begin measuringtime durations for instances of requests 752. Responsive to suchrequests, synthetic application 722 may initiate resource consumptionsof node 716. After completing resource consumptions of node 716,synthetic application 722 may send replies 754 to synthetic application720. Synthetic application 720 may finish measuring time durations foreach request 752 based upon replies 754. Synthetic application 720 maysend replies 756 to synthetic application 718. Synthetic application 718may finish measuring time durations for each request 750 based uponreplies 756. Synthetic application 720, may send time duration data 790measured by synthetic application 720 to synthetic application 718.Synthetic application 718 may store time duration data 790 and 792measured by synthetic applications 720 and 718 in storage 780 or memoryof node 712.

As shown in FIG. 7B, synthetic application 718 may be configured togenerate additional instances of synthetic application definitions basedupon any suitable expected change in real-world application behavior.For example, synthetic application 718 may be configured to generatesynthetic application definition 706 based upon synthetic application704. Synthetic application 718 may generate synthetic applicationdefinition 706 by modifying any suitable portion of syntheticapplication definition 704, such as workloads, business functions, orregistries.

In one embodiment, synthetic application definition 706 may includemodified business functions. If, for example, particular groups of nodesdesignated for hosting portions of real-world applications are expectedto see increased, decreased or changed levels of user-demand, businessfunctions of synthetic application 706 representing these portions maybe modified to include more, fewer, or different nodes. Syntheticapplication definition 706 may further include a modified registryincluding lists of additional or different nodes and addressescorresponding to those nodes. Additionally, synthetic applicationdefinition 706 may include a modified Mix of business functions, and/ormodified mix parameters or associated mix values.

In another embodiment, synthetic application definition 706 may includemodified workloads. For example, values associated with parameters suchas WorkloadIterations, WorkloadDelay, WorkloadReqSize,WorkloadConcurrency, WorkloadKind may be modified to reflect an expectedbehavior of a real-world application at a different level of userdemand. In yet another embodiment, node properties included in syntheticapplication definition 704 may be modified. For example valuesassociated with parameters such as ThreadLimit, FanOuts,SerialExecution, ReadBytes, ReadLoops, CPUConsume, ReqSizes, ReplyBytes,ReqMemBytes, AppMemBytes, or Tokens may be modified to reflect anexpected behavior of a real-world application at a different level ofuser demand

After generating synthetic application definition 706, syntheticapplication 718 may parse synthetic application definition 706.Synthetic application 718 may distribute node 784A and 784B propertiesto synthetic application 720 in node 714, and synthetic application 722in node 716, respectively. Although a particular number andconfiguration of nodes of cloud 702 is shown in FIG. 7B, it will beunderstood that more, fewer or different nodes may be included insynthetic application definition 706. Based upon synthetic applicationdefinition 706, instances of synthetic applications may consumeresources of any suitable node.

Once nodes described in business functions of synthetic applicationdefinition 704 have node properties, synthetic application 718 may sendone or more requests 758 to synthetic application 720. Syntheticapplication 718 may begin measuring time durations 796 for instances ofrequests 758. Responsive to such requests, synthetic application 720 mayinitiate resource consumptions of node 714. Based upon businessfunctions in synthetic application definition 704, synthetic application720 may send one or more requests 760. In one embodiment, requests 760may be sent via a network to synthetic application 722. In anotherembodiment, if business functions of synthetic application definition706 are different from business functions of synthetic applicationdefinition 704, requests 760 may be sent to any specified syntheticapplication in any suitable node. Synthetic application 720 may beginmeasuring time durations 794 for instances of requests 752.

Responsive to such requests, synthetic application 722 may initiateresource consumptions of node 716. After completing resourceconsumptions of node 716, synthetic application 722 may send replies762. In one embodiment, replies 762 may be sent via a network tosynthetic application 720. In another embodiment, if business functionsof synthetic application definition 706 are different from businessfunctions of synthetic application definition 704, replies 762 may besent to any specified synthetic application in any suitable node.Synthetic application 720 may finish measuring time durations 794 foreach request 760 based upon replies 762. Synthetic application 720 maysend replies 764 to synthetic application 718. Synthetic application 718may finish measuring time durations 796 for each request 758 based uponreplies 764. Synthetic application 720 may send time duration data 794measured by synthetic application 720 to synthetic application 718.Synthetic application 718 may store time duration data 794 and 796measured by synthetic applications 720 and 718 in storage 780 or memoryof node 712.

Although a particular number and configuration of nodes is depicted inFIG. 7B, it will be understood that synthetic application 718 mayconsume resources of any suitable node in response to syntheticapplication definition 706. It will also be understood that differencesbetween business functions depicted in FIGS. 7A and 7B are exemplary,and that any suitable modifications may be made to a syntheticapplication definition. Further, although synthetic application 718 isdescribed as generating synthetic application definition 706, it will beunderstood that any suitable node or portion of node, whether includedin cloud 702 or not, may be used to generate synthetic applicationdefinition 706.

Using time duration data measured from resource consumptions effectuatedbased on synthetic application definitions 704 and 706, performancecharacteristics of a real-world application at multiple levels of userdemand may be evaluated. For example, time durations derived fromsynthetic application definitions 706 may be compared to time durationsderived from synthetic application definitions 704 to estimate changesin performance. Time durations derived from synthetic applicationdefinitions 706 may be compared to a threshold performance requirement.Comparisons may be implemented using processing, memory, or storageresources of any suitable node. For example, one or more nodes in system700 may include computer program code for comparing time durations data790 or 792 to time duration data 794 or 796. In other embodiments, oneor more nodes in system 700 may include computer program code forcomparing time durations data 790, 792, 794 or 796 to threshold timeduration values.

Based on time durations data 790, 792, 794 or 796, system 700 mayevaluate whether changes reflected in synthetic application definitions706 are acceptable. For example, differences between time durations data790, 792, 794 or 796 may be compared to thresholds establishing whetherchanges in response time represent suitable performance changes. If suchchanges in response time represent suitable performance changes, thenreal applications represented by synthetic application definitions 706may be used on cloud 702.

System 700 may consume any suitable analysis of time durations data 790,792, 794 or 796 to launch the operation of real-world applications uponwhich synthetic application definitions 704, 706 are based. For example,if the footprint of a real-world application needs to increase, asrepresented by changes in requirements of synthetic applicationdefinition 706 over synthetic application definition 704, system 700 mayanalyze resulting time durations data 790, 792, 794 or 796. If such dataindicates that operation based upon synthetic application definition 706meets performance thresholds, then system 700 may launch a real-worldapplication on cloud 702 with a footprint matching that in syntheticapplication definition 706.

FIG. 8 is a flowchart of an exemplary method 800 for performingapplication-specific assessment of cloud hosting suitability formultiple applications, in accordance with teachings of the presentdisclosure. Although FIG. 8 discloses a particular number of steps to betaken with respect to exemplary method 800, method 800 may be executedwith more or fewer steps than those depicted in FIG. 8. In addition,although FIG. 8 discloses a certain order of steps to be taken withrespect to method 800, the steps of these methods may be completed inany suitable order. Method 800 may be implemented using the system ofFIGS. 1-5, 7, 9, 11, 13, or any other suitable mechanism. In certainembodiments, method 800 may be implemented partially or fully insoftware embodied in computer-readable storage media. Method 800 may beprovided as a computer program product that may include one or moremachine readable media having stored thereon instructions that may beused to program a processing system or other electronic device toperform the methods.

Method 800 may begin, for example, at step 805 with the creation of asynthetic application definition. The synthetic application definitionmay describe sequences of resource consumptions which approximate thebehavior of a particular real-world application or group ofapplications.

At step 810, additional synthetic applications may be created based uponany suitable expected change in application behavior, such as anincrease, decrease, or change in user demand. For example, additionalsynthetic applications may be scaled by increasing, decreasing, and/ormodifying any suitable parameter of a synthetic application, such asworkloads, business functions, registries, or default parameters.

At step 815, synthetic applications may be deployed to various nodes ofa computing system, for example computing system 700 of FIG. 7A and 7B.Nodes may include, for example, a server (e.g., blade server or rackserver), personal computer (e.g., desktop or laptop), tablet computer,mobile device (e.g., personal digital assistant (PDA) or smart phone),network storage device, printer, switch, router, data collection device,virtual machine, script, executable, firmware, library, shared library,function, module, software application, or any other suitable device orapplication. Synthetic applications may be deployed to nodes by use of anetwork or any other suitable means of deploying synthetic applications.

At step 820, synthetic application definitions may be introduced to oneor more synthetic applications of nodes of a computing system, forexample synthetic application definition 704 or 706 of FIGS. 7A and 7Brespectively. Synthetic application definitions may be distributed tonodes by use of a network or any other suitable means of deployingsynthetic application definition. An instance of synthetic applicationto which a synthetic application definition is distributed may bereferred to as a master instance of synthetic application.

At step 825, synthetic application modules of a synthetic applicationmay parse a synthetic application definition. Parsing a syntheticapplication definition may include parsing a registry, parsing businessfunctions, parsing node properties, or referring to default parametersto supply parameter values, as shown, for example, in FIGS. 1, 5, 6, and7.

At step 830, synthetic application modules may distribute nodeproperties to other instances of synthetic application modules. Forexample, node properties may be distributed to one or more instances ofsynthetic application described in child flows of node properties. Nodeproperties may be distributed to instances of synthetic applications viaa network or any other suitable means of distribution.

At step 835, synthetic application modules may commence consumingresources of a computing system. Instances of synthetic applicationmodules may consume resources of nodes of a computing system. Forexample, synthetic application modules may consume processing resources,storage resources, memory resources, network resources, and/or any othersuitable resource associated with nodes of a computing system. Resourceconsumption may be effectuated based upon parameters included in nodeproperties. Consumption of resources may begin, for example, by one ormore master instances of synthetic application issuing resourceconsumption requests according to workloads in synthetic applicationsdefinitions. Issuing consumption requests may also include beginningdata collection of time durations between requests and replies.

At step 840, after completing resource consumptions of nodes of acomputing system, synthetic application modules may send replies toparent instances of synthetic application modules. Receipt of repliesmay initiate recording of time duration data between requests andreplies. Time duration data may be stored in a storage resource of anode, as shown in FIG. 7.

At step 845, if sufficient time duration data to compare performance ofapplications in a particular cloud at varying demand levels isavailable, the method may proceed to step 850. If sufficient data is notavailable, the method may return to step 820, where a new syntheticapplication definition may be deployed. Sufficient data may be availablewhen multiple versions of a synthetic application definition have beenused to generate time duration data. Any suitable number of syntheticapplications may be used.

At step 850, time duration data corresponding to instances of syntheticapplication definitions may be evaluated. For example, time durationdata corresponding to one synthetic application may be compared to timeduration data corresponding to a different synthetic application. Inother embodiments, time duration data corresponding to a syntheticapplication may be compared to threshold performance requirements. Anysuitable method of evaluating time duration data may be used. Method 800may repeat with different synthetic applications, or different syntheticapplication definitions, or may terminate.

FIG. 9 is an illustration of an exemplary system 900 for performingapplication-specific assessment of cloud hosting suitability of multipleclouds, in accordance with teachings of the present disclosure. System900, as shown in FIG. 9, may include clouds 902 and 904. In someembodiments, system 900 may be configured to effectuate resourceconsumptions of nodes in clouds 902 and 904. Cloud 902 may include nodes912 and 914. Nodes 912 and 914 may include synthetic applications 916and 918 respectively. Cloud 904 may include nodes 942, and 944. Nodes942 and 944 may include synthetic applications 946 and 948 respectively.In some embodiments, synthetic application definition 980 may begenerated by modifying a base synthetic application definition toreflect a new expected level of user demand. In other embodiments,synthetic application definition 980 may be chosen to represent anysuitable real-world application behavior.

In some embodiments of the invention, synthetic applications may beconfigured to estimate the performance of a real-world application inmore than one cloud. A particular cloud hosting a real-world applicationmay be unsuitable or less suitable than another cloud for a variety ofreasons. For example, if a third-party is purchasing infrastructure as aservice and user demand drops, an application may be moved to anothercloud to save infrastructure costs. If user demand increases, anapplication may be moved to another cloud provisioned with greaterresources to maintain sufficient response times. For any suitablereason, it may be desirable to estimate the performance of a real-worldapplication on more than one cloud by using synthetic applications.Synthetic applications in different clouds may be configured based on asynthetic application definition describing resource consumptions of aparticular real-world application.

Evaluation of performance goals or other execution metrics of clouds 902or 904 may be performed in any suitable manner. In one embodiment,evaluation of execution may be made by measuring response times forgiven business functions or other operations to be executed by syntheticapplications 916 or 918 in cloud 902, or synthetic applications 946 or948 in cloud 904. Response times may include time required to propagateinformation between synthetic applications 916, 918 or 946, 948 as wellas time required for each synthetic application 916, 918, 946, 948 toperform specified tasks.

Synthetic application definition 980 may be introduced to syntheticapplication 916 in node 912. Synthetic application 916 may parsesynthetic application definition 980. Synthetic application 916 maydistribute node properties 982 to synthetic application 918 in node 914.Once nodes described in business functions of synthetic applicationdefinition 980 have node properties, synthetic application 912 may,based upon business functions in synthetic application definition 980,send one or more requests 950 to synthetic application 918. Syntheticapplication 912 may begin measuring time durations 984 for instances ofrequests 950. Responsive to such requests, synthetic application 918 mayinitiate resource consumptions of node 914. After completing resourceconsumptions, synthetic application 918 may send replies 952 tosynthetic application 916. Synthetic application 916 may finishmeasuring time durations 984 for each request 950 based upon replies952. Synthetic application 916 may store time duration data 984 measuredby synthetic application 916 in storage or memory of node 912.

Synthetic application definition 980 may be introduced to syntheticapplication 946 in node 942. Synthetic application 946 may parsesynthetic application definition 980. Synthetic application 946 maydistribute node properties 982 to synthetic application 948 in node 944.Once nodes described in business functions of synthetic applicationdefinition 980 have node properties, synthetic application 942 may,based upon business functions in synthetic application definition 980,send one or more requests 954 to synthetic application 948. Syntheticapplication 942 may begin measuring time durations 986 for instances ofrequests 954. Responsive to such requests, synthetic application 948 mayinitiate resource consumptions of node 944. After completing resourceconsumptions, synthetic application 948 may send replies 956 tosynthetic application 946. Synthetic application 946 may finishmeasuring time durations 986 for each request 954 based upon replies956. Synthetic application 946 may store time duration data 986 measuredby synthetic application 946 in storage 960 or memory of node 942.

Using time duration data 984 and 986 measured from resource consumptionseffectuated based on synthetic application definitions 980 in clouds 902and 904, performance characteristics of a real-world application inmultiple cloud may be evaluated. For example, time durations 984 derivedfrom synthetic application definitions 980 in cloud 902 may be comparedto time durations 986 derived from synthetic application definitions 980in cloud 904 to estimate differences in performance. Time durations 984and 986 derived from synthetic application definitions 980 may becompared to threshold performance requirements. Comparisons may beimplemented using processing, memory, network, or storage resources ofany suitable node. For example, one or more nodes in system 900 mayinclude computer program code for comparing time duration data 984 totime duration data 986. In other embodiments, one or more nodes insystem 900 may include computer program code for comparing timedurations data 984 or 986 to threshold time duration values.

Based upon comparisons of time durations 984, 986 with thresholdperformance requirements, system 900 may deploy a real-world applicationto a selected one of clouds 902, 904. Furthermore, based upon suchcomparisons, system 900 may move a real-world application from cloud 902to cloud 904, or vice-versa. The real-world application may include anapplication upon which synthetic application definitions 980 is based.

In one embodiment, if cost of operation of cloud 902 is greater thancloud 904, and synthetic applications in cloud 904 operate withinperformance thresholds, system 900 may launch the real-world applicationin cloud 904. In another embodiment, if synthetic applications in cloud902 do not meet performance thresholds but the same syntheticapplication in cloud 904 meets performance threshold, system 900 maylaunch the real-world application in cloud 904. In yet anotherembodiment, clouds 902, 904 are both available to execute a real-worldapplication, system 900 may launch the real-world application in the oneof clouds 902, 904 that has the best performance of the same syntheticapplication. Such a best performance may be rated by, for example,response times.

FIG. 10 is a flowchart of an exemplary method 1000 for operating anapplication-specific assessment of cloud hosting suitability of multipleclouds, in accordance with the teachings of the present disclosure.Although FIG. 10 discloses a particular number of steps to be taken withrespect to exemplary method 1000, method 1000 may be executed with moreor fewer steps than those depicted in FIG. 10. In addition, althoughFIG. 10 discloses a certain order of steps to be taken with respect tomethod 1000, the steps of these methods may be completed in any suitableorder. Method 1000 may be implemented using the system of FIGS. 1-5, 7,9, 11, 13, or any other suitable mechanism. In certain embodiments,method 1000 may be implemented partially or fully in software embodiedin computer-readable storage media. Method 1000 may be provided as acomputer program product that may include one or more machine readablemedia having stored thereon instructions that may be used to program aprocessing system or other electronic device to perform the methods.

Method 1000 may begin, for example, at step 1005 with the creation of asynthetic application definition. Synthetic application definition maydescribe sequences of resource consumptions which approximate thebehavior of a particular real-world application or group ofapplications.

At step 1010, synthetic applications may be deployed to a cloud, forexample cloud 902 or 904 of FIG. 9. Nodes may include, for example, aserver (e.g., blade server or rack server), personal computer (e.g.,desktop or laptop), tablet computer, mobile device (e.g., personaldigital assistant (PDA) or smart phone), network storage device,printer, switch, router, data collection device, virtual machine,script, executable, firmware, library, shared library, function, module,software application, or any other suitable device or application.Synthetic applications may be deployed to nodes by use of a network orany other suitable means of deploying synthetic applications.

At step 1015, synthetic application definitions may be introduced to oneor more synthetic applications of nodes of a cloud, for examplesynthetic application definition 980 of FIG. 9. Synthetic applicationdefinitions may be distributed to nodes by use of a network or any othersuitable means of deploying synthetic application definition. Aninstance of synthetic application to which a synthetic applicationdefinition is distributed may be referred to as a master instance ofsynthetic application.

At step 1020, synthetic application modules of a synthetic applicationmay parse a synthetic application definition. Parsing a syntheticapplication definition may include parsing a registry, parsing businessfunctions, parsing node properties, or referring to default parametersto supply parameter values, as shown, for example, in FIGS. 1, 5, 6, and9.

At step 1025, synthetic application modules may distribute nodeproperties to other instances of synthetic application modules. Forexample, node properties may be distributed to one or more instances ofsynthetic application described in child flows of node properties. Nodeproperties may be distributed to instances of synthetic applications viaa network or any other suitable means of distribution.

At step 1030, synthetic application modules may commence consumingresources of a computing system. Instances of synthetic applicationmodules may consume resources of nodes of a computing system. Forexample, synthetic application modules may consume processing resources,storage resources, memory resources, network resources, and/or any othersuitable resource associated with nodes of a computing system. Resourceconsumption may be effectuated based upon parameters included in nodeproperties. Consumption of resources may begin, for example, by one ormore master instances of synthetic application issuing resourceconsumption requests according to workloads in synthetic applicationsdefinitions. Issuing consumption requests may also include beginningdata collection of time durations between requests and replies.

At step 1035, after completing resource consumptions of nodes of acomputing system, synthetic application modules may send replies toparent instances of synthetic application modules. Receipt of repliesmay initiate recording of time duration data between requests andreplies. Time duration data may be stored in a storage resource of anode, as shown in FIG. 9.

At step 1040, if sufficient time duration data to compare performance ofan application in one or more clouds is available, the method mayproceed to step 1045. If sufficient data is not available, the methodmay return to step 1010, where a new synthetic application may bedeployed to one or more different clouds. A synthetic application may bedeployed to the different clouds in step 1115. Sufficient data may beavailable when a synthetic application definition has been used togenerate time duration data in multiple clouds. Any suitable number ofsynthetic applications or clouds may be used.

At step 1045, time duration data corresponding to resource consumptionsaccording to synthetic application definitions in multiple clouds may beevaluated. For example, time duration data corresponding to a syntheticapplication definition in one cloud may be compared to time durationdata corresponding to a synthetic application definition in a differentcloud. In other embodiments, time duration data corresponding to asynthetic application in a particular cloud may be compared to thresholdperformance requirements. Any suitable method of evaluating timeduration data may be used. Method 1000 may repeat with differentsynthetic applications, different synthetic application definitions,different clouds, or different nodes, or may terminate.

FIG. 11 is an illustration of an exemplary system 1100 for performingapplication-specific assessment of cloud hosting suitability formultiple applications in a node of a cloud, in accordance with teachingsof the present disclosure. System 1100, as shown in FIG. 11, may includeclouds 1102. System 1100 may be configured to effectuate resourceconsumptions of nodes in clouds 1102. Cloud 1102 may include nodes 1104,1106, and 1008. Nodes 1104 and 1106 may include synthetic applications1110 and 1112, respectively. Node 1108 may include syntheticapplications 1114 and 1116. Node 1108 may include associated processor1126, storage 1128, and/or memory 1130.

In some embodiments of the invention, synthetic applications may beconfigured to estimate performance impacts of hosting multipleapplications or portions of applications in a single node. A particularreal-world application may share computing resources of nodes with otherreal-world applications. For example, if a third-party customerpurchases Infrastructure as a Service from a vendor of cloud services,the vendor may host multiple third-party applications on a singlephysical node. For example, physical nodes may host multiple virtualmachine nodes. In another example, if a third-party is purchasingInfrastructure as a Service, a particular set of physical resources maybe allocated to a particular virtual machine. It may be desirable toestimate the impact of including more, fewer, or different combinationsof applications within a particular virtual machine, on a particularhost, or in a particular cloud. In one embodiment of the invention,multiple instances of synthetic applications configured to representvirtual machines may be deployed in a single physical node.

Additionally, particular physical nodes may be designated to hostmultiple real-world applications. In one embodiment of the invention,multiple instances of synthetic applications within a single node may beconfigured based on synthetic application definitions describingresource consumptions of one or more real-world applications. For anysuitable reason, it may be desirable to estimate the performance of areal-world application sharing computing resources with other real-worldapplications.

In one embodiment of the invention, synthetic application definitions1118 and 1120 may be introduced to synthetic applications 1110 and 1112,respectively. Synthetic applications 1110 and 1112 may parse syntheticapplication definitions 1118 and 1120, respectively. Syntheticapplication 1110 may distribute node properties 1122 to syntheticapplication 1114 in node 1108. Synthetic application 1112 may distributenode properties 1124 to synthetic application 1116 in node 1108. Onceinstances of synthetic applications described in business functions ofsynthetic application definitions 1118 and 1120 have node properties,synthetic applications 1110 and 1112 may, based upon business functionsin synthetic application definitions 1118 and 1120, respectively, beginconsuming resources of nodes in cloud 1102. For example, syntheticapplication 1110 may send one or more requests 1132 to syntheticapplication 1114. Synthetic application 1112 may send one or morerequests 1136 to synthetic application 1116. Synthetic applications 1110and 1112 may begin measuring time durations for instances of requests1132 1136, respectively. Responsive to such requests, syntheticapplications 1114 and 1116 may initiate resource consumptions of node1108. For example, synthetic application 1114 may consume processingresources 1126, storage resources 1128, and/or memory resources 1130.Synthetic application 1116 may consume processing resources 1126,storage resources 1128, and/or memory resources 1130.

After completing resource consumptions, synthetic applications 1114 and1116 may send replies 1134 and 1138 to synthetic applications 1110 and1112, respectively. Synthetic application 1110 may finish measuring timedurations for each request 1132 based upon replies 1134. Syntheticapplication 1112 may finish measuring time durations for each request1136 based upon replies 1138. Synthetic application 1110 may store timeduration data measured by synthetic application 1110 in storage ormemory of node 1104. Synthetic application 1112 may store time durationdata measured by synthetic application 1112 in storage or memory of node1106.

Using time duration data measured from resource consumptions effectuatedbased on synthetic application definitions 1118 and 1120 in cloud 1102,performance characteristics of multiple real-world applications in acloud may be evaluated. For example, time durations derived fromsynthetic applications 1118 1120 may be compared to a thresholdperformance requirement. Comparisons may be implemented usingprocessing, memory, or storage resources of any suitable node. Forexample, one or more nodes in system 1100 may include computer programcode for evaluating time duration data. In other embodiments, one ormore nodes in system 1100 may include computer program code forcomparing time durations data to threshold time duration values. Basedupon comparisons of time durations with threshold performancerequirements, system 1100 may deploy a selected number of instances ofreal-world applications to a node, such as node 1108. Instances ofreal-world applications may include applications upon which syntheticapplication definitions 1118 and 1120 are based.

In one embodiment, if a number of synthetic applications in cloud 1102operate within performance thresholds, system 1100 may launch a similarnumber of real-world applications in cloud 1102. In another embodiment,if synthetic applications in cloud 1102 do not meet performancethresholds, system 1100 may launch fewer instances of real-worldapplications in cloud 1102.

FIG. 12 is a flowchart of an exemplary method 1200 for performingapplication-specific assessment of cloud hosting suitability of multipleapplications in a node of a cloud, in accordance with teachings of thepresent disclosure. Although FIG. 12 discloses a particular number ofsteps to be taken with respect to exemplary method 1200, method 1200 maybe executed with more or fewer steps than those depicted in FIG. 12. Inaddition, although FIG. 12 discloses a certain order of steps to betaken with respect to method 1200, the steps of these methods may becompleted in any suitable order. Method 1200 may be implemented usingthe system of FIGS. 1-5, 7, 9, 11, 13, or any other suitable mechanism.In certain embodiments, method 1200 may be implemented partially orfully in software embodied in computer-readable storage media. Method1200 may be provided as a computer program product that may include oneor more machine readable media having stored thereon instructions thatmay be used to program a processing system or other electronic device toperform the methods.

Method 1200 may begin, for example, at step 1205 with the creation of asynthetic application definition. Synthetic application definition maydescribe sequences of resource consumptions which approximate thebehavior of a particular real-world application or group ofapplications.

At step 1210, synthetic applications may be deployed to a cloud, forexample cloud 1102 of FIG. 11. Nodes may include, for example, a server(e.g., blade server or rack server), personal computer (e.g., desktop orlaptop), tablet computer, mobile device (e.g., personal digitalassistant (PDA) or smart phone), network storage device, printer,switch, router, data collection device, virtual machine, script,executable, firmware, library, shared library, function, module,software application, or any other suitable device or application.Synthetic applications may be deployed to nodes by use of a network orany other suitable means of deploying synthetic applications.

At step 1215, one or more additional instances of synthetic applicationsmay be deployed to particular nodes in the cloud, for example node 1108of FIG. 11. Synthetic applications may be deployed to nodes by use of anetwork or any other suitable means of deploying synthetic applications.Synthetic applications may be deployed to nodes by use of a network orany other suitable means of deploying synthetic applications.

At step 1220, synthetic application definitions may be introduced to oneor more synthetic applications of nodes of a cloud, for examplesynthetic application definition 1118 or 1120 of FIG. 11. Syntheticapplication definitions may be distributed to nodes by use of a networkor any other suitable means of deploying synthetic applicationdefinition. An instance of synthetic application to which a syntheticapplication definition is distributed may be referred to as a masterinstance of synthetic application.

At step 1225, synthetic application modules of a synthetic applicationmay parse a synthetic application definition. Parsing a syntheticapplication definition may include parsing a registry, parsing businessfunctions, parsing node properties, or referring to default parametersto supply parameter values, as shown, for example, in FIGS. 1, 5, 6, and11.

At step 1230, synthetic application modules may distribute nodeproperties to other instances of synthetic application modules. Forexample, node properties may be distributed to one or more instances ofsynthetic application described in child flows of node properties. Nodeproperties may be distributed to instances of synthetic applications viaa network or any other suitable means of distribution.

At step 1235, synthetic application modules may commence consumingresources of a computing system. Instances of synthetic applicationmodules may consume resources of nodes of a computing system. Forexample, synthetic application modules may consume processing resources,storage resources, memory resources, network resources, and/or any othersuitable resource associated with nodes of a computing system. Resourceconsumption may be effectuated based upon parameters included in nodeproperties. Consumption of resources may begin, for example, by one ormore master instances of synthetic application issuing resourceconsumption requests according to workloads in synthetic applicationsdefinitions. Issuing consumption requests may also include beginningdata collection of time durations between requests and replies.

At step 1240, after completing resource consumptions of nodes of acomputing system, synthetic application modules may send replies toparent instances of synthetic application modules. Receipt of repliesmay initiate recording of time duration data between requests andreplies. Time duration data may be stored in a storage resource of anode, as shown in FIG. 7 or 9.

At step 1245, time duration data corresponding to resource consumptionsaccording to synthetic application definitions in multiple clouds may beevaluated. For example, time duration data corresponding to a syntheticapplication definition in one cloud may be compared to time durationdata corresponding to a synthetic application definition in a differentcloud. In other embodiments, time duration data corresponding to asynthetic application in a particular cloud may be compared to thresholdperformance requirements. Any suitable method of evaluating timeduration data may be used. Method 1200 may repeat with differentsynthetic applications, different synthetic application definitions, ordifferent nodes, or may terminate.

FIG. 13 is an illustration of an exemplary system 1300 for performingservice-level agreement (SLA) assessment of a cloud. An SLA may definecapacities, capabilities, or configurations of a cloud such as cloud1302 that are to be available for users of cloud 1302. An SLA may begranted by, for example, a service provider to customers who pay for useof cloud 1302. The capacities, capabilities, or configurations of cloud1302 may be specified by an SLA in any suitable manner, such asprocessing capabilities, overall network throughput, node-to-nodenetwork throughput, storage space, temporal requirements, responsetimes, uptime, failure rates, data rates, or minimum or averagerequirements.

Cloud 1302 may include any suitable number of nodes, such as nodes 1312,1314. Nodes 1312 and 1314 may include synthetic applications 1316 and1318, respectively.

Synthetic application 1316 may be configured as a master instance of asynthetic application. Furthermore, synthetic application 1316 may beconfigured to coordinate service-level agreement assessment of cloud1302. Synthetic application 1316 may be configured to assess cloud 1302in any suitable manner. In one embodiment, synthetic application 1316may apply synthetic application definition 1306 to the syntheticapplication instances of cloud 1302.

In one embodiment, synthetic application definition 1306 may begenerated from requirements specified in an SLA 1308. SLA 1308 maydefine capacities, capabilities, or configurations of cloud 1302 thatare to be available to users of cloud 1302 as described above. Syntheticapplication definition 1306 may include specification of operations ofsynthetic applications 1316, 1318 that are configured to meet or exceedthe capacities, capabilities, or configurations defined in SLA 1308.

For example, SLA 1308 may define that network throughput between node1312 and 1314 must be at least a certain bandwidth X. Syntheticapplication definition 1306 may specify operation of syntheticapplications 1316 and 1318 to exchange network traffic such thatbandwidth X should be reached. Response times may be measured at each ofsynthetic applications 1316 and 1318 to measure actual bandwidth usedduring such an evaluation.

In another example, SLA 1308 may define that synthetic application 1318must be able to sustain a certain number of writes Y to storage asreceived from synthetic application 1316 within a designated time frame,thus performing a business function of network shared storage. Syntheticapplication definition 1306 may specify operation of syntheticapplication 1316 to send information to synthetic application 1318 whichmay perform an associated number of writes to storage. Syntheticapplications 1316, 1318 may record the time for their operations andstore them as time data 1390 in, for example, storage 1380.

In other embodiments, synthetic application definition 1306 may begenerated based upon a real-world application which is the subject ofSLA 1308. Synthetic application definition 1306 may then be used tocharacterize the capabilities of a particular cloud to execute areal-world application in compliance with SLA 1308.

Comparisons of performance of cloud 1302 to requirements of SLA 1308 maybe made by, for example, synthetic application 1316 or any othersuitable portion of system 1300.

Synthetic application definition 1306 may be introduced to syntheticapplication 1316 in node 1312. Synthetic application 1316 may parsesynthetic application definition 1306. Synthetic application may performoperations defined in synthetic application definition 1306 for variousbusiness functions, such as consumption of resource of node 1312 orcommunication with other nodes. Synthetic application 1316 maydistribute node properties 1322 to synthetic application 1318 in node1314. Synthetic application 1316 may send one or more requests tosynthetic application 1318. Synthetic application 1316 may beginmeasuring time durations for instances of the requests. Responsive tosuch requests, synthetic application 1318 may initiate resourceconsumptions of node 1314. Synthetic application 1318 may send repliesto synthetic application 1316. Synthetic application 1316 may finishmeasuring time data 1390 for requests and store time data 1390 instorage 1380. Additional properties may be issued to other syntheticapplication instances in cloud 1302 as defined by synthetic applicationdefinition 1306.

Any errors, time-outs, or other performance messages encountered duringexecution of synthetic applications 1316, 1318 may be reported tosynthetic application 1316 and stored in storage 1380 as errors 1392.Such messages may arise, for example, from unavailability of a softwareor hardware node of cloud 1302 for a request from a syntheticapplication instance.

Using time data 1390, performance abilities of cloud 1302 may beevaluated. Such evaluations may be made by any suitable portion ofsystem 1300, such as synthetic application 1316. In one embodiment, timedata 1390 may be compared against performance thresholds to determinewhether responses were made in accordance with requirements specified inSLA 1308. If time data 1390 meets such performance thresholds, thencloud 1302 may be providing services in accordance with SLA 1308. Inanother embodiment, errors 1392 may be analyzed to determine whether anyrequirements of SLA 1308 as specified in synthetic applicationdefinition 1306 have been missed during operation of syntheticapplications 1316, 1318. If no requirements of SLA 1308 have beenmissed, then performance of cloud 1302 may be verified. Otherwise,failures of cloud 1302 may be identified through time data 1390 orerrors 1392. The characteristics causing time data 1390 or errors 1392may be identified as possible culprits for the failure of cloud 1302 toprovide adequate service.

FIG. 14 is a flowchart of an exemplary method 1400 for performingservice-level agreement assessment of a cloud. Although FIG. 14discloses a particular number of steps to be taken with respect toexemplary method 1400, method 1400 may be executed with more or fewersteps than those depicted in FIG. 14. In addition, although FIG. 14discloses a certain order of steps to be taken with respect to method1400, the steps of these methods may be completed in any suitable order.Method 1400 may be implemented using the system of FIGS. 1-5, 7, 9, 11,13, or any other suitable mechanism. In certain embodiments, method 1400may be implemented partially or fully in software embodied incomputer-readable storage media. Method 1400 may be provided as acomputer program product that may include one or more machine readablemedia having stored thereon instructions that may be used to program aprocessing system or other electronic device to perform the methods.

Method 1400 may begin, for example, at step 1405 with the determinationof a set of criteria for an SLA defined in a digital format. The SLA mayspecify minimum resource levels that are to be available on a cloud.Such a definition may include, for example, a file, record, datastructure, database entry, or any other suitable format.

At step 1410, a synthetic application definition may be created from theSLA requirements. Synthetic application definition may describesequences of resource consumptions which meet the specific resource SLArequirements. These may approximate the behavior of a particularreal-world application or group of applications.

At step 1415, synthetic applications may be deployed to a cloud, such ascloud 1302 of FIG. 13. Nodes may include, for example, a server (e.g.,blade server or rack server), personal computer (e.g., desktop orlaptop), tablet computer, mobile device (e.g., personal digitalassistant (PDA) or smart phone), network storage device, printer,switch, router, data collection device, virtual machine, script,executable, firmware, library, shared library, function, module,software application, or any other suitable device or application.Synthetic applications may be deployed to nodes by use of a network orany other suitable means of deploying synthetic applications. One ormore additional instances of synthetic applications may be deployed toparticular nodes in the cloud, if specified in the synthetic applicationdefinition.

At step 1420, synthetic application definitions may be introduced to oneor more synthetic applications of nodes of a cloud, for examplesynthetic application definition 1306 of FIG. 13. Synthetic applicationdefinitions may be distributed to nodes by use of a network or any othersuitable means of deploying synthetic application definition. Aninstance of synthetic application to which a synthetic applicationdefinition is distributed may be referred to as a master instance ofsynthetic application.

At step 1425, synthetic application modules of a synthetic applicationmay parse a synthetic application definition. Parsing a syntheticapplication definition may include parsing a registry, parsing businessfunctions, parsing node properties, or referring to default parametersto supply parameter values.

At step 1430, synthetic application modules may distribute nodeproperties to other instances of synthetic application modules. Forexample, node properties may be distributed to one or more instances ofsynthetic application described in child flows of node properties. Nodeproperties may be distributed to instances of synthetic applications viaa network or any other suitable means of distribution.

At step 1435, synthetic application modules may commence consumingresources of a computing system. Instances of synthetic applicationmodules may consume resources of nodes of a computing system. Forexample, synthetic application modules may consume processing resources,storage resources, memory resources, network resources, and/or any othersuitable resource associated with nodes of a computing system. Resourceconsumption may be effectuated based upon parameters included in nodeproperties. Consumption of resources may begin, for example, by one ormore master instances of synthetic application issuing resourceconsumption requests according to workloads in synthetic applicationsdefinitions. Issuing consumption requests may also include beginningdata collection of time durations between requests and replies.Synthetic application modules may send replies to parent instances ofsynthetic application modules. Receipt of replies may initiate recordingof time duration data between requests and replies.

At step 1440, time duration data may be stored in a storage resource ofa node, as shown in FIG. 7, 9, or 13. Furthermore, any executionmessages, errors, or time-outs may be stored. The time duration data andexecution messages may be based upon execution of synthetic applicationsto perform their specified tasks.

At step 1445, data collected during execution may be evaluated. If anyerrors have been encountered, method 1400 may proceed to step 1460.Otherwise, method 1400 may proceed to step 1450. At step 1450, it may bedetermined whether execution of synthetic operations was completedwithin designated performance thresholds. Such thresholds may beestablished by, for example, derivation of requirements from the SLA. Ifthe time thresholds are met by the recorded time data, then method 1400may proceed to step 1455. Otherwise, method 1400 may proceed to step1460.

At step 1455, it may be determined that the cloud upon which thesynthetic applications executed meets SLA requirements. At step 1460, itmay be determined that the cloud upon which the synthetic applicationsexecuted fails the SLA requirements. Method 1400 may repeat withdifferent definitions or SLA requirements or may terminate.

The flowcharts and block diagrams in the figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods and computer program products according to variousaspects of the present disclosure. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof code, which comprises one or more executable instructions forimplementing the specified logical function(s). It should also be notedthat, in some implementations, the functions noted in the block mayoccur out of the order noted in the figures. For example, two blocksshown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. It will also be notedthat each block of the block diagrams and/or flowchart illustration, andcombinations of blocks in the block diagrams and/or flowchartillustration, can be implemented by special purpose hardware-basedsystems that perform the specified functions or acts, or combinations ofspecial purpose hardware and computer instructions.

The terminology used herein is for the purpose of describing particularaspects only and is not intended to be limiting of the disclosure. Asused herein, the singular forms “a,” “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, nodes, and/orcomponents, but do not preclude the presence or addition of one or moreother features, integers, steps, operations, nodes, components, and/orgroups thereof.

The corresponding structures, materials, acts, and equivalents of anymeans or step plus function nodes in the claims below are intended toinclude any disclosed structure, material, or act for performing thefunction in combination with other claimed nodes as specificallyclaimed. The description of the present disclosure has been presentedfor purposes of illustration and description, but is not intended to beexhaustive or limited to the disclosure in the form disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of thedisclosure. The aspects of the disclosure herein were chosen anddescribed in order to best explain the principles of the disclosure andthe practical application, and to enable others of ordinary skill in theart to understand the disclosure with various modifications as aresuited to the particular use contemplated.

What is claimed is:
 1. A method comprising: defining a first pluralityof resource consumptions in a first synthetic application definition,wherein the first plurality of resource consumptions are equivalent toconsumptions by a candidate application at a first level of user demand;distributing the first synthetic application definition to a syntheticapplication; consuming, with the synthetic application and based on thefirst synthetic application definition, a first plurality of quantitiesof resources of a plurality of nodes of a computing system; recording afirst performance of the synthetic application; creating a secondsynthetic application definition based on the first syntheticapplication definition, wherein creating the second applicationdefinition comprises defining, in the second synthetic applicationdefinition, a second plurality of resource consumptions, wherein thesecond plurality of resource consumptions are equivalent to consumptionsby the candidate application at a second level of user demand;distributing the second synthetic application definition to thesynthetic application; consuming, with the synthetic application andbased on the second synthetic application definition, a second pluralityof quantities of resources of the plurality of nodes of the computingsystem; recording a second performance of the synthetic application; andevaluating the computing system based upon the first performance and thesecond performance.
 2. The method of claim 1, wherein creating thesecond synthetic application definition based on the first syntheticapplication definition further comprises scaling a consumption value ofthe first synthetic application definition.
 3. The method of claim 1,wherein creating the second synthetic application definition based onthe first synthetic application definition further comprises adding abusiness function to the first synthetic application definition.
 4. Themethod of claim 1, wherein: the first synthetic application definitioncomprises a business function with an associated execution proportion;and creating the second synthetic application definition based on thefirst synthetic application definition further comprises altering theassociated execution proportion.
 5. The method of claim 1, whereincreating the second synthetic application definition based on the firstsynthetic application definition further comprises altering a workloadparameter.
 6. The method of claim 1, wherein: recording the firstperformance of the synthetic application comprises storing a firstdistribution of response times; recording the second performance of thesynthetic application comprises storing a second distribution ofresponse times; and evaluating the computer system based upon the firstperformance and the second performance comprises comparing the firstdistribution of response times and the second distribution of responsetimes.
 7. The method of claim 1, wherein: recording the firstperformance of the synthetic application comprises storing a firstdistribution of response times; recording the second performance of thesynthetic application comprises storing a second distribution ofresponse times; and evaluating the computer system based upon the firstperformance and the second performance comprises comparing the seconddistribution of response times to a performance requirement.
 8. Acomputer-readable storage medium, comprising computer-executableinstructions carried on the computer readable medium, the instructionsreadable by a processor and, when read and executed, configured to causethe processor to: define a first plurality of resource consumptions in afirst synthetic application definition, wherein the first plurality ofresource consumptions are equivalent to consumptions by a candidateapplication at a first level of user demand; distribute the firstsynthetic application definition to a synthetic application; consume,with the synthetic application and based on the first syntheticapplication definition, a first plurality of quantities of resources ofa plurality of nodes of a computing system; record a first performanceof the synthetic application; create a second synthetic applicationdefinition based on the first synthetic application definition, whereincreating the second application definition comprises defining, in thesecond synthetic application definition, a second plurality of resourceconsumptions, wherein the second plurality of resource consumptions areequivalent to consumptions by the candidate application at a secondlevel of user demand; distribute the second synthetic applicationdefinition to the synthetic application; consume, with the syntheticapplication and based on the second synthetic application definition, asecond plurality of quantities of resources of the plurality of nodes ofthe computing system; record a second performance of the syntheticapplication; and evaluate the computing system based upon the firstperformance and the second performance.
 9. The computer-readable storagemedium of claim 8, wherein creating the second synthetic applicationdefinition based on the first synthetic application definition furthercomprises scaling a consumption value of the first synthetic applicationdefinition.
 10. The computer-readable storage medium of claim 8, whereincreating the second synthetic application definition based on the firstsynthetic application definition further comprises adding a businessfunction to the first synthetic application definition.
 11. Thecomputer-readable storage medium of claim 8, wherein: the firstsynthetic application definition comprises a business function with anassociated execution proportion; and creating the second syntheticapplication definition based on the first synthetic applicationdefinition further comprises altering the associated executionproportion.
 12. The computer-readable storage medium of claim 8,wherein: recording the first performance of the synthetic applicationcomprises storing a first distribution of response times; recording thesecond performance of the synthetic application comprises storing asecond distribution of response times; and evaluating the computersystem based upon the first performance and the second performancecomprises comparing the first distribution of response times and thesecond distribution of response times.
 13. The computer-readable storagemedium of claim 8, wherein: recording the first performance of thesynthetic application comprises storing a first distribution of responsetimes; recording the second performance of the synthetic applicationcomprises storing a second distribution of response times; andevaluating the computer system based upon the first performance and thesecond performance comprises comparing the second distribution ofresponse times to a performance requirement.
 14. An apparatus forassessing cloud hosting suitability of a plurality of nodes of acomputer system, the apparatus comprising: a processor; and a memorycommunicatively coupled to the processor, the memory comprisinginstructions operable, when executed for causing the processor to:define a first plurality of resource consumptions in a first syntheticapplication definition, wherein the first plurality of resourceconsumptions are equivalent to consumptions by a candidate applicationat a first level of user demand; distribute the first syntheticapplication definition to a synthetic application; consume, with thesynthetic application and based on the first synthetic applicationdefinition, a first plurality of quantities of resources of a pluralityof nodes of a computing system; record a first performance of thesynthetic application; create a second synthetic application definitionbased on the first synthetic application definition, wherein creatingthe second application definition comprises defining, in the secondsynthetic application definition, a second plurality of resourceconsumptions, wherein the second plurality of resource consumptions areequivalent to consumptions by the candidate application at a secondlevel of user demand; distribute the second synthetic applicationdefinition to the synthetic application; consume, with the syntheticapplication and based on the second synthetic application definition, asecond plurality of quantities of resources of the plurality of nodes ofthe computing system; record a second performance of the syntheticapplication; and evaluate the computing system based upon the firstperformance and the second performance.
 15. The apparatus of claim 14,wherein creating the second synthetic application definition based onthe first synthetic application definition further comprises scaling aconsumption value of the first synthetic application definition.
 16. Theapparatus of claim 14, wherein creating the second synthetic applicationdefinition based on the first synthetic application definition furthercomprises adding a business function to the first synthetic applicationdefinition.
 17. The apparatus of claim 14, wherein: the first syntheticapplication definition comprises a business function with an associatedexecution proportion; and creating the second synthetic applicationdefinition based on the first synthetic application definition furthercomprises altering the associated execution proportion.
 18. Theapparatus of claim 14, wherein creating the second synthetic applicationdefinition based on the first synthetic application definition furthercomprises altering a workload parameter.
 19. The apparatus of claim 14,wherein: recording the first performance of the synthetic applicationcomprises storing a first distribution of response times; recording thesecond performance of the synthetic application comprises storing asecond distribution of response times; and evaluating the computersystem based upon the first performance and the second performancecomprises comparing the first distribution of response times and thesecond distribution of response times.
 20. The apparatus of claim 14,wherein: recording the first performance of the synthetic applicationcomprises storing a first distribution of response times; recording thesecond performance of the synthetic application comprises storing asecond distribution of response times; and evaluating the computersystem based upon the first performance and the second performancecomprises comparing the second distribution of response times to aperformance requirement.